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Merge tag 'v0.8.0'

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This commit is contained in:
Paul Romano 2016-07-25 10:09:32 -05:00
commit 85c5070923
529 changed files with 56604 additions and 28204 deletions
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16
.gitignore vendored
View file

@ -15,8 +15,9 @@ openmc.egg-info/
# Inputs generated from Python API
examples/python/**/*.xml
# emacs backups
# emacs and vim backups
*~
*.swp
# OpenMC statepoints
*.binary
@ -24,6 +25,8 @@ examples/python/**/*.xml
# Documentation builds
docs/build
docs/source/_images/*.pdf
docs/source/_images/*.aux
docs/source/pythonapi/generated/
# Source build
build
@ -41,6 +44,8 @@ results_test.dat
# Test build files
tests/build/
tests/coverage/
tests/memcheck/
tests/ctestscript.run
# HDF5 files
@ -53,11 +58,14 @@ src/bin/
src/cmake_install.cmake
src/install_manifest.txt
# Data downloaded from NNDC
# Nuclear data
data/nndc
data/wmp
data/multipole_lib.tar.gz
#Images
# Images
*.ppm
*.voxel
# PyCharm project configuration files
.idea
@ -73,4 +81,4 @@ docs/source/pythonapi/examples/*.xls
docs/source/pythonapi/examples/mgxs
docs/source/pythonapi/examples/tracks
docs/source/pythonapi/examples/fission-rates
docs/source/pythonapi/examples/plots
docs/source/pythonapi/examples/plots

7
.travis.yml
View file

@ -27,7 +27,7 @@ before_install:
- conda config --set always_yes yes --set changeps1 no
- conda update -q conda
- conda info -a
- conda create -q -n test-environment python=$TRAVIS_PYTHON_VERSION numpy scipy h5py pandas
- conda create -q -n test-environment python=$TRAVIS_PYTHON_VERSION numpy scipy h5py=2.5 pandas
- source activate test-environment
# Install GCC, MPICH, HDF5, PHDF5
@ -44,7 +44,10 @@ before_script:
- git clone --branch=master git://github.com/bhermanmit/nndc_xs nndc_xs
- cat nndc_xs/nndc.tar.gza* | tar xzvf -
- rm -rf nndc_xs
- export CROSS_SECTIONS=$PWD/nndc/cross_sections.xml
- export OPENMC_CROSS_SECTIONS=$PWD/nndc/cross_sections.xml
- git clone --branch=master git://github.com/smharper/windowed_multipole_library.git wmp_lib
- tar xzvf wmp_lib/multipole_lib.tar.gz
- export OPENMC_MULTIPOLE_LIBRARY=$PWD/multipole_lib
- cd ..
script:

141
CMakeLists.txt
View file

@ -1,5 +1,5 @@
cmake_minimum_required(VERSION 2.8 FATAL_ERROR)
project(openmc Fortran)
project(openmc Fortran C)
# Setup output directories
set(CMAKE_ARCHIVE_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
@ -107,50 +107,62 @@ if(CMAKE_Fortran_COMPILER_ID STREQUAL GNU)
message(FATAL_ERROR "gfortran version must be 4.6 or higher")
endif()
# GNU Fortran compiler options
# GCC compiler options
list(APPEND f90flags -cpp -std=f2008 -fbacktrace)
list(APPEND cflags -cpp -std=c99)
if(debug)
if(NOT (GCC_VERSION VERSION_LESS 4.7))
list(APPEND f90flags -Wall)
list(APPEND cflags -Wall)
endif()
list(APPEND f90flags -g -pedantic -fbounds-check
-ffpe-trap=invalid,overflow,underflow)
list(APPEND cflags -g -pedantic -fbounds-check)
list(APPEND ldflags -g)
endif()
if(profile)
list(APPEND f90flags -pg)
list(APPEND cflags -pg)
list(APPEND ldflags -pg)
endif()
if(optimize)
list(APPEND f90flags -O3)
list(APPEND cflags -O3)
endif()
if(openmp)
list(APPEND f90flags -fopenmp)
list(APPEND cflags -fopenmp)
list(APPEND ldflags -fopenmp)
endif()
if(coverage)
list(APPEND f90flags -coverage)
list(APPEND cflags -coverage)
list(APPEND ldflags -coverage)
endif()
elseif(CMAKE_Fortran_COMPILER_ID STREQUAL Intel)
# Intel Fortran compiler options
# Intel compiler options
list(APPEND f90flags -fpp -std08 -assume byterecl -traceback)
list(APPEND cflags -std=c99)
if(debug)
list(APPEND f90flags -g -warn -ftrapuv -fp-stack-check
"-check all" -fpe0)
list(APPEND cflags -g -w3 -ftrapuv -fp-stack-check)
list(APPEND ldflags -g)
endif()
if(profile)
list(APPEND f90flags -pg)
list(APPEND cflags -pg)
list(APPEND ldflags -pg)
endif()
if(optimize)
list(APPEND f90flags -O3)
list(APPEND cflags -O3)
endif()
if(openmp)
list(APPEND f90flags -openmp)
list(APPEND ldflags -openmp)
list(APPEND f90flags -qopenmp)
list(APPEND cflags -qopenmp)
list(APPEND ldflags -qopenmp)
endif()
elseif(CMAKE_Fortran_COMPILER_ID STREQUAL PGI)
@ -243,6 +255,12 @@ add_subdirectory(src/xml/fox)
# which point to directories outside the build tree to the install RPATH
set(CMAKE_INSTALL_RPATH_USE_LINK_PATH TRUE)
#===============================================================================
# Build faddeeva library
#===============================================================================
add_library(faddeeva STATIC src/Faddeeva.c)
#===============================================================================
# Build OpenMC executable
#===============================================================================
@ -263,11 +281,14 @@ endif()
# set compile flags. Note that this sets the COMPILE_OPTIONS property (also
# available only in 2.8.12+) rather than the COMPILE_FLAGS property, which is
# deprecated. The former can handle lists whereas the latter cannot.
if(CMAKE_VERSION VERSION_LESS 4.8.12)
if (CMAKE_VERSION VERSION_LESS 2.8.12)
string(REPLACE ";" " " f90flags "${f90flags}")
string(REPLACE ";" " " cflags "${cflags}")
set_property(TARGET ${program} PROPERTY COMPILE_FLAGS "${f90flags}")
set_property(TARGET faddeeva PROPERTY COMPILE_FLAGS "${cflags}")
else()
target_compile_options(${program} PUBLIC ${f90flags})
target_compile_options(faddeeva PRIVATE ${cflags})
endif()
# Add HDF5 library directories to link line with -L
@ -277,7 +298,7 @@ endforeach()
# target_link_libraries treats any arguments starting with - but not -l as
# linker flags. Thus, we can pass both linker flags and libraries together.
target_link_libraries(${program} ${ldflags} ${HDF5_LIBRARIES} fox_dom)
target_link_libraries(${program} ${ldflags} ${HDF5_LIBRARIES} fox_dom faddeeva)
#===============================================================================
# Install executable, scripts, manpage, license
@ -296,6 +317,7 @@ if(PYTHONINTERP_FOUND)
--root=debian/openmc --install-layout=deb
WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR})")
else()
install(CODE "set(ENV{PYTHONPATH} \"${CMAKE_INSTALL_PREFIX}/lib/python${PYTHON_VERSION_MAJOR}.${PYTHON_VERSION_MINOR}/site-packages\")")
install(CODE "execute_process(
COMMAND ${PYTHON_EXECUTABLE} setup.py install
--prefix=${CMAKE_INSTALL_PREFIX}
@ -313,113 +335,36 @@ include(CTest)
# Get a list of all the tests to run
file(GLOB_RECURSE TESTS ${CMAKE_CURRENT_SOURCE_DIR}/tests/test_*.py)
# Check for MEM_CHECK and COVERAGE variables
if (DEFINED ENV{MEM_CHECK})
set(MEM_CHECK $ENV{MEM_CHECK})
else(DEFINED ENV{MEM_CHECK})
set(MEM_CHECK FALSE)
endif(DEFINED ENV{MEM_CHECK})
if (DEFINED ENV{COVERAGE})
set(COVERAGE $ENV{COVERAGE})
else(DEFINED ENV{COVERAGE})
set(COVERAGE FALSE)
endif(DEFINED ENV{COVERAGE})
# Loop through all the tests
foreach(test ${TESTS})
# Get test information
get_filename_component(TEST_NAME ${test} NAME)
get_filename_component(TEST_PATH ${test} PATH)
# Check for running standard tests (no valgrind, no gcov)
if(NOT ${MEM_CHECK} AND NOT ${COVERAGE})
if (DEFINED ENV{MEM_CHECK})
# Generate input files if needed
if (NOT EXISTS "${TEST_PATH}/geometry.xml")
execute_process(COMMAND ${PYTHON_EXECUTABLE} ${TEST_NAME} --build-inputs
WORKING_DIRECTORY ${TEST_PATH})
endif()
# Add serial test
add_test(NAME ${TEST_NAME}
WORKING_DIRECTORY ${TEST_PATH}
COMMAND $<TARGET_FILE:openmc>)
else()
# Check serial/parallel
if (${MPI_ENABLED})
# Preform a parallel test
add_test(NAME ${TEST_NAME}
WORKING_DIRECTORY ${TEST_PATH}
COMMAND ${PYTHON_EXECUTABLE} ${TEST_NAME} --exe $<TARGET_FILE:openmc>
--mpi_exec $ENV{MPI_DIR}/bin/mpiexec)
else(${MPI_ENABLED})
else()
# Perform a serial test
add_test(NAME ${TEST_NAME}
WORKING_DIRECTORY ${TEST_PATH}
COMMAND ${PYTHON_EXECUTABLE} ${TEST_NAME} --exe $<TARGET_FILE:openmc>)
endif(${MPI_ENABLED})
# Handle special case for valgrind and gcov (run openmc directly, no python)
else(NOT ${MEM_CHECK} AND NOT ${COVERAGE})
# If a plot test is encountered, run with "-p"
if (${test} MATCHES "test_plot")
# Perform serial valgrind and coverage test with plot flag
add_test(NAME ${TEST_NAME}
WORKING_DIRECTORY ${TEST_PATH}
COMMAND $<TARGET_FILE:openmc> -p ${TEST_PATH})
elseif(${test} MATCHES "test_filter_distribcell")
# Add each case for distribcell tests
add_test(NAME ${TEST_NAME}_case-1
WORKING_DIRECTORY ${TEST_PATH}/case-1
COMMAND $<TARGET_FILE:openmc> ${TEST_PATH}/case-1)
add_test(NAME ${TEST_NAME}_case-2
WORKING_DIRECTORY ${TEST_PATH}/case-2
COMMAND $<TARGET_FILE:openmc> ${TEST_PATH}/case-2)
add_test(NAME ${TEST_NAME}_case-3
WORKING_DIRECTORY ${TEST_PATH}/case-3
COMMAND $<TARGET_FILE:openmc> ${TEST_PATH}/case-3)
add_test(NAME ${TEST_NAME}_case-4
WORKING_DIRECTORY ${TEST_PATH}/case-4
COMMAND $<TARGET_FILE:openmc> ${TEST_PATH}/case-4)
# If a restart test is encounted, need to run with -r and restart file(s)
elseif(${test} MATCHES "restart")
# Handle restart tests separately
if(${test} MATCHES "test_statepoint_restart")
set(RESTART_FILE statepoint.07.h5)
elseif(${test} MATCHES "test_sourcepoint_restart")
set(RESTART_FILE statepoint.07.h5 source.07.h5)
elseif(${test} MATCHES "test_particle_restart_eigval")
set(RESTART_FILE particle_9_555.h5)
elseif(${test} MATCHES "test_particle_restart_fixed")
set(RESTART_FILE particle_7_928.h5)
else(${test} MATCHES "test_statepoint_restart")
message(FATAL_ERROR "Restart test ${test} not recognized")
endif(${test} MATCHES "test_statepoint_restart")
# Perform serial valgrind and coverage test
add_test(NAME ${TEST_NAME}
WORKING_DIRECTORY ${TEST_PATH}
COMMAND $<TARGET_FILE:openmc> ${TEST_PATH})
# Perform serial valgrind and coverage restart test
add_test(NAME ${TEST_NAME}_restart
WORKING_DIRECTORY ${TEST_PATH}
COMMAND $<TARGET_FILE:openmc> -r ${RESTART_FILE} ${TEST_PATH})
# Set test dependency
set_tests_properties(${TEST_NAME}_restart PROPERTIES DEPENDS ${TEST_NAME})
# Handle standard tests for valgrind and gcov
else(${test} MATCHES "test_plot")
# Perform serial valgrind and coverage test
add_test(NAME ${TEST_NAME}
WORKING_DIRECTORY ${TEST_PATH}
COMMAND $<TARGET_FILE:openmc> ${TEST_PATH})
endif(${test} MATCHES "test_plot")
endif(NOT ${MEM_CHECK} AND NOT ${COVERAGE})
endif()
endif()
endforeach(test)

2
LICENSE
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@ -1,4 +1,4 @@
Copyright (c) 2011-2015 Massachusetts Institute of Technology
Copyright (c) 2011-2016 Massachusetts Institute of Technology
Permission is hereby granted, free of charge, to any person obtaining a copy of
this software and associated documentation files (the "Software"), to deal in

125
data/get_multipole_data.py Executable file
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@ -0,0 +1,125 @@
#!/usr/bin/env python
from __future__ import print_function
import os
import shutil
import subprocess
import sys
import tarfile
import glob
import hashlib
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('-b', '--batch', action='store_true',
help='supresses standard in')
args = parser.parse_args()
try:
from urllib.request import urlopen
except ImportError:
from urllib2 import urlopen
cwd = os.getcwd()
sys.path.insert(0, os.path.join(cwd, '..'))
baseUrl = 'https://github.com/smharper/windowed_multipole_library/blob/master/'
files = ['multipole_lib.tar.gz?raw=true']
checksums = ['3985aea96f7162a9419c7ed8352e6abb']
block_size = 16384
# ==============================================================================
# DOWNLOAD FILES FROM GITHUB REPO
filesComplete = []
for f in files:
# Establish connection to URL
url = baseUrl + f
req = urlopen(url)
# Get file size from header
if sys.version_info[0] < 3:
file_size = int(req.info().getheaders('Content-Length')[0])
else:
file_size = req.length
downloaded = 0
# Remove GitHub junk from the file name.
fname = f[:-9] if f.endswith('?raw=true') else f
# Check if file already downloaded
if os.path.exists(fname):
if os.path.getsize(fname) == file_size:
print('Skipping ' + fname)
filesComplete.append(fname)
continue
else:
if sys.version_info[0] < 3:
overwrite = raw_input('Overwrite {0}? ([y]/n) '.format(fname))
else:
overwrite = input('Overwrite {0}? ([y]/n) '.format(fname))
if overwrite.lower().startswith('n'):
continue
# Copy file to disk
print('Downloading {0}... '.format(f), end='')
with open(fname, 'wb') as fh:
while True:
chunk = req.read(block_size)
if not chunk: break
fh.write(chunk)
downloaded += len(chunk)
status = '{0:10} [{1:3.2f}%]'.format(downloaded, downloaded * 100. / file_size)
print(status + chr(8)*len(status), end='')
print('')
filesComplete.append(fname)
# ==============================================================================
# VERIFY MD5 CHECKSUMS
print('Verifying MD5 checksums...')
for f, checksum in zip(files, checksums):
fname = f[:-9] if f.endswith('?raw=true') else f
downloadsum = hashlib.md5(open(fname, 'rb').read()).hexdigest()
if downloadsum != checksum:
raise IOError("MD5 checksum for {} does not match. If this is your first "
"time receiving this message, please re-run the script. "
"Otherwise, please contact OpenMC developers by emailing "
"openmc-users@googlegroups.com.".format(f))
# ==============================================================================
# EXTRACT FILES FROM TGZ
for f in files:
fname = f[:-9] if f.endswith('?raw=true') else f
if fname not in filesComplete:
continue
# Extract files
with tarfile.open(fname, 'r') as tgz:
print('Extracting {0}...'.format(fname))
tgz.extractall(path='wmp/')
# Move data files down one level
for filename in glob.glob('wmp/multipole_lib/*'):
shutil.move(filename, 'wmp/')
os.rmdir('wmp/multipole_lib')
# ==============================================================================
# PROMPT USER TO DELETE .TAR.GZ FILES
# Ask user to delete
if not args.batch:
if sys.version_info[0] < 3:
response = raw_input('Delete *.tar.gz files? ([y]/n) ')
else:
response = input('Delete *.tar.gz files? ([y]/n) ')
else:
response = 'y'
# Delete files if requested
if not response or response.lower().startswith('y'):
for f in files:
if os.path.exists(f):
print('Removing {0}...'.format(f))
os.remove(f)

8
data/get_nndc_data.py
View file

@ -11,8 +11,8 @@ import hashlib
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('-b', '--batch', action = 'store_true',
help = 'supresses standard in')
parser.add_argument('-b', '--batch', action='store_true',
help='supresses standard in')
args = parser.parse_args()
try:
@ -84,13 +84,13 @@ for f, checksum in zip(files, checksums):
raise IOError("MD5 checksum for {} does not match. If this is your first "
"time receiving this message, please re-run the script. "
"Otherwise, please contact OpenMC developers by emailing "
"openmc-users@googlegroups.com.")
"openmc-users@googlegroups.com.".format(f))
# ==============================================================================
# EXTRACT FILES FROM TGZ
for f in files:
if not f in filesComplete:
if f not in filesComplete:
continue
# Extract files

9
docs/Makefile
View file

@ -17,6 +17,8 @@ ALLSPHINXOPTS = -d $(BUILDDIR)/doctrees $(PAPEROPT_$(PAPER)) $(SPHINXOPTS) sou
SVG2PDF = inkscape
PDFS = $(patsubst %.svg,%.pdf,$(wildcard $(IMAGEDIR)/*.svg))
# Tikz to PNG conversion
PNGS = $(patsubst %.tex,%.png,$(wildcard $(IMAGEDIR)/*.tex))
.PHONY: help images clean html dirhtml singlehtml pickle json htmlhelp qthelp devhelp epub latex latexpdf text man changes linkcheck doctest
@ -43,8 +45,13 @@ help:
%.pdf: %.svg
$(SVG2PDF) -f $< -A $@
%.png: %.tex
pdflatex --interaction=nonstopmode --output-directory=$(IMAGEDIR) $<
pdftoppm -r 120 -singlefile $(patsubst %.tex,%.pdf, $<) $(basename $<)
convert -trim -fuzz 2% -transparent white $(patsubst %.tex,%.ppm,$<) $@
# Rule to build PDFs
images: $(PDFS)
images: $(PDFS) $(PNGS)
clean:
-rm -rf $(BUILDDIR)/*

2
docs/requirements-rtd.txt Normal file
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@ -0,0 +1,2 @@
sphinx-numfig
jupyter

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12
docs/source/methods/cmfd_tikz/cmfd_flow.tikz → docs/source/_images/cmfd_flow.tex
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@ -1,3 +1,12 @@
\documentclass{standalone}
\usepackage[utf8]{inputenc}
\usepackage{amsmath}
\usepackage{tikz}
\usepackage{pgfplots}
\pgfplotsset{compat=1.11}
\usetikzlibrary{shapes,snakes,shadows,arrows,calc,decorations.markings,patterns,fit,matrix,spy}
\pagestyle{empty}
\begin{document}
\begin{tikzpicture}
\matrix[every node/.style={draw, thick, minimum width=3cm, minimum height=1cm, align=center}, column sep=2cm, row sep=1cm] (m) {
\node[draw, fill=red!40] (start) {Batch $i$ \\ tally NDA}; & \\
@ -16,4 +25,5 @@
\draw (modify.north) -- (end.south);
\end{scope}
\end{tikzpicture}
\end{tikzpicture}
\end{document}

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41
docs/source/methods/cmfd_tikz/meshfig.tikz → docs/source/_images/meshfig.tex
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@ -1,10 +1,20 @@
\documentclass[tikz]{standalone}
\usepackage[utf8]{inputenc}
\usepackage{amsmath}
\usepackage{tikz}
\usepackage{pgfplots}
\pgfplotsset{compat=1.11}
\usetikzlibrary{shapes,snakes,shadows,arrows,calc,decorations.markings,patterns,fit,matrix,spy}
\usepackage{fixltx2e}
\pagestyle{empty}
\begin{document}
% these dimensions are determined in arrow_dimms.ods
\def\scale{1.0}
\def\latWidth{0.2808363589*\scale}
\def\RPVOR{3*\scale}
\def\rectW{0.75*\scale}
\def\RPVIR{2.8694005485*\scale}
@ -20,7 +30,7 @@
\def\bafMIRy{1.5445999739*\scale}
\def\bafMORx{1.8544620609*\scale}
\def\bafMORy{1.573625702*\scale}
\tikzset{Assembly/.style={
inner sep=0pt,
text width=\latWidth in,
@ -29,13 +39,13 @@
align=center
}
}
\def\tkzRPV{(0,0) circle (\RPVIR) (0,0) circle (\RPVOR)}
\def\tkzBarrel{(0,0) circle (\BarrelIR) (0,0) circle (\BarrelOR)}
\def\tkzShields{(0,0) circle (\BarrelOR) (0,0) circle (\ShieldOR)}
\def\tkzBaffCOR{(-\bafCORx, -\bafCORy) rectangle (\bafCORx, \bafCORy)}
\def\tkzBaffCIR{(-\bafCIRx, -\bafCIRy) rectangle (\bafCIRx, \bafCIRy)}
\def\tkzBaffCIR{(-\bafCIRx, -\bafCIRy) rectangle (\bafCIRx, \bafCIRy)}
\def\tkzBaffMOR{(-\bafMORx, -\bafMORy) rectangle (\bafMORx, \bafMORy)}
\def\tkzBaffMIR{(-\bafMIRx, -\bafMIRy) rectangle (\bafMIRx, \bafMIRy) }
\def\tkzBaffleC{ \tkzBaffCIR \tkzBaffCOR }
@ -53,7 +63,7 @@
\begin{tikzpicture}[x=1in,y=1in, xshift=3in]
\scalebox{0.6}{
% draw RPV, barrel, and shield panels
\path[fill=black,even odd rule] \tkzRPV;
\path[fill=black,even odd rule] \tkzBarrel;
\begin{scope}
@ -61,9 +71,9 @@
\path[fill=black,even odd rule] \tkzShields;
\end{scope}
% draw assembly row/column headers
\draw[red, thick] ($(-7*\latWidth,\RPVOR/\latWidth*\latWidth)$) node[above, anchor=south] {R} -- ($(-7*\latWidth,4*\latWidth)$);
\draw[red, thick] ($(-6*\latWidth,\RPVOR/\latWidth*\latWidth)$) node[above, anchor=south] {P} -- ($(-6*\latWidth,6*\latWidth)$);
\draw[red, thick] ($(-5*\latWidth,\RPVOR/\latWidth*\latWidth)$) node[above, anchor=south] {N} -- ($(-5*\latWidth,7*\latWidth)$);
@ -79,7 +89,7 @@
\draw[red, thick] ($(5*\latWidth,\RPVOR/\latWidth*\latWidth)$) node[above, anchor=south] {C} -- ($(5*\latWidth,7*\latWidth)$);
\draw[red, thick] ($(6*\latWidth,\RPVOR/\latWidth*\latWidth)$) node[above, anchor=south] {B} -- ($(6*\latWidth,6*\latWidth)$);
\draw[red, thick] ($(7*\latWidth,\RPVOR/\latWidth*\latWidth)$) node[above, anchor=south] {A} -- ($(7*\latWidth,4*\latWidth)$);
\begin{scope}[rotate=90]
\draw[red, thick] ($(-7*\latWidth,\RPVOR/\latWidth*\latWidth)$) node[left, anchor=east] {15} -- ($(-7*\latWidth,4*\latWidth)$);
\draw[red, thick] ($(-6*\latWidth,\RPVOR/\latWidth*\latWidth)$) node[left, anchor=east] {14} -- ($(-6*\latWidth,6*\latWidth)$);
@ -97,7 +107,7 @@
\draw[red, thick] ($(6*\latWidth,\RPVOR/\latWidth*\latWidth)$) node[left, anchor=east] {2} -- ($(6*\latWidth,6*\latWidth)$);
\draw[red, thick] ($(7*\latWidth,\RPVOR/\latWidth*\latWidth)$) node[left, anchor=east] {1} -- ($(7*\latWidth,4*\latWidth)$);
\end{scope}
% draw fuel assembly nodes
\node [Assembly, fill=\lightgray, opacity=0.3] at ($(-8*\latWidth,8*\latWidth)$) {};
\node [Assembly, fill=\lightgray, opacity=0.3] at ($(-7*\latWidth,8*\latWidth)$) {};
@ -116,7 +126,7 @@
\node [Assembly, fill=\lightgray, opacity=0.3] at ($( 6*\latWidth,8*\latWidth)$) {};
\node [Assembly, fill=\lightgray, opacity=0.3] at ($( 7*\latWidth,8*\latWidth)$) {};
\node [Assembly, fill=\lightgray, opacity=0.3] at ($( 8*\latWidth,8*\latWidth)$) {};
\node [Assembly, fill=\lightgray, opacity=0.3] at ($(-8*\latWidth,7*\latWidth)$) {};
\node [Assembly, fill=\lightgray, opacity=0.3] at ($(-7*\latWidth,7*\latWidth)$) {};
\node [Assembly, fill=\lightgray, opacity=0.3] at ($(-6*\latWidth,7*\latWidth)$) {};
@ -581,7 +591,7 @@
\node [Assembly, fill=\lightgray, opacity=0.3] at ($( 6*\latWidth,-7*\latWidth)$) {};
\node [Assembly, fill=\lightgray, opacity=0.3] at ($( 7*\latWidth,-7*\latWidth)$) {};
\node [Assembly, fill=\lightgray, opacity=0.3] at ($( 8*\latWidth,-7*\latWidth)$) {};
\node [Assembly, fill=\lightgray, opacity=0.3] at ($(-8*\latWidth,-8*\latWidth)$) {};
\node [Assembly, fill=\lightgray, opacity=0.3] at ($(-7*\latWidth,-8*\latWidth)$) {};
\node [Assembly, fill=\lightgray, opacity=0.3] at ($(-6*\latWidth,-8*\latWidth)$) {};
@ -601,7 +611,7 @@
\node [Assembly, fill=\lightgray, opacity=0.3] at ($( 8*\latWidth,-8*\latWidth)$) {};
% draw baffle north/south
\begin{scope}[even odd rule]
\clip[rotate=90] \tkzBaffMClip;
\path[fill=black] \tkzBaffleC;
@ -611,9 +621,9 @@
\clip \tkzBaffMClip;
\path[fill=black, rotate=90] \tkzBaffleM;
\end{scope}
% draw baffle east/west
\begin{scope}[rotate=90]
\begin{scope}[even odd rule]
\clip[rotate=90] \tkzBaffMClip;
@ -626,3 +636,4 @@
\end{scope}
\end{scope}}
\end{tikzpicture}
\end{document}

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10
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@ -0,0 +1,10 @@
/* override table width restrictions */
.wy-table-responsive table td, .wy-table-responsive table th {
white-space: normal;
}
.wy-table-responsive {
margin-bottom: 24px;
max-width: 100%;
overflow: visible;
}

7
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@ -0,0 +1,7 @@
{{ fullname }}
{{ underline }}
.. currentmodule:: {{ module }}
.. autoclass:: {{ objname }}
:members:

8
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@ -0,0 +1,8 @@
{{ fullname }}
{{ underline }}
.. currentmodule:: {{ module }}
.. autoclass:: {{ objname }}
:members:
:inherited-members:

6
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@ -0,0 +1,6 @@
{{ fullname }}
{{ underline }}
.. currentmodule:: {{ module }}
.. autofunction:: {{ objname }}

65
docs/source/conf.py
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@ -13,6 +13,21 @@
import sys, os
# Determine if we're on Read the Docs server
on_rtd = os.environ.get('READTHEDOCS', None) == 'True'
# On Read the Docs, we need to mock a few third-party modules so we don't get
# ImportErrors when building documentation
try:
from unittest.mock import MagicMock
except ImportError:
from mock import Mock as MagicMock
MOCK_MODULES = ['numpy', 'h5py', 'pandas', 'opencg']
sys.modules.update((mod_name, MagicMock()) for mod_name in MOCK_MODULES)
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
@ -26,9 +41,10 @@ sys.path.insert(0, os.path.abspath('../..'))
# coming with Sphinx (named 'sphinx.ext.*') or your custom ones.
extensions = ['sphinx.ext.autodoc',
'sphinx.ext.napoleon',
'sphinx.ext.pngmath',
'sphinx.ext.mathjax',
'sphinx.ext.autosummary',
'sphinxcontrib.tikz',
'sphinx.ext.intersphinx',
'sphinx.ext.viewcode',
'sphinx_numfig',
'notebook_sphinxext']
@ -46,16 +62,16 @@ master_doc = 'index'
# General information about the project.
project = u'OpenMC'
copyright = u'2011-2015, Massachusetts Institute of Technology'
copyright = u'2011-2016, Massachusetts Institute of Technology'
# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
# built documents.
#
# The short X.Y version.
version = "0.7"
version = "0.8"
# The full version, including alpha/beta/rc tags.
release = "0.7.1"
release = "0.8.0"
# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
@ -103,21 +119,13 @@ pygments_style = 'tango'
# -- Options for HTML output ---------------------------------------------------
# The theme to use for HTML and HTML Help pages. Major themes that come with
# Sphinx are currently 'default' and 'sphinxdoc'.
html_theme = 'haiku'
#html_theme = 'altered_nature'
#html_theme = 'sphinxdoc'
# The theme to use for HTML and HTML Help pages
if not on_rtd:
import sphinx_rtd_theme
html_theme = 'sphinx_rtd_theme'
html_theme_path = [sphinx_rtd_theme.get_html_theme_path()]
# Theme options are theme-specific and customize the look and feel of a theme
# further. For a list of options available for each theme, see the
# documentation.
html_theme_options = {'full_logo': True,
'linkcolor': '#0c3762',
'visitedlinkcolor': '#0c3762'}
# Add any paths that contain custom themes here, relative to this directory.
#html_theme_path = ["_theme"]
html_logo = '_images/openmc200px.png'
# The name for this set of Sphinx documents. If None, it defaults to
# "<project> v<release> documentation".
@ -126,10 +134,6 @@ html_title = "OpenMC Documentation"
# A shorter title for the navigation bar. Default is the same as html_title.
#html_short_title = None
# The name of an image file (relative to this directory) to place at the top
# of the sidebar.
html_logo = '_images/openmc.png'
# The name of an image file (within the static path) to use as favicon of the
# docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32
# pixels large.
@ -138,7 +142,10 @@ html_logo = '_images/openmc.png'
# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
#html_static_path = ['_static']
html_static_path = ['_static']
def setup(app):
app.add_stylesheet('theme_overrides.css')
# If not '', a 'Last updated on:' timestamp is inserted at every page bottom,
# using the given strftime format.
@ -231,4 +238,12 @@ latex_elements = {
#Autodocumentation Flags
#autodoc_member_order = "groupwise"
#autoclass_content = "both"
#autosummary_generate = []
autosummary_generate = True
napoleon_use_ivar = True
intersphinx_mapping = {
'python': ('https://docs.python.org/3', None),
'numpy': ('http://docs.scipy.org/doc/numpy/', None),
'pandas': ('http://pandas.pydata.org/pandas-docs/stable/', None)
}

11
docs/source/devguide/docbuild.rst
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@ -12,15 +12,8 @@ is via pip:
sudo pip install sphinx
Additionally, you will also need two Sphinx extensions for TikZ support and
numbering figures. The sphinxcontrib-tikz_ package should be installed directly
from the git repository as such:
.. code-block:: sh
sudo pip install https://bitbucket.org/philexander/tikz/get/HEAD.tar.gz
The Numfig_ package can be installed directly with pip:
Additionally, you will also need a Sphinx extension for numbering figures. The
Numfig_ package can be installed directly with pip:
.. code-block:: sh

13
docs/source/index.rst
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@ -4,19 +4,23 @@ The OpenMC Monte Carlo Code
OpenMC is a Monte Carlo particle transport simulation code focused on neutron
criticality calculations. It is capable of simulating 3D models based on
constructive solid geometry with second-order surfaces. The particle interaction
data is based on ACE format cross sections, also used in the MCNP and Serpent
Monte Carlo codes.
constructive solid geometry with second-order surfaces. OpenMC supports either
continuous-energy or multi-group transport. The continuous-energy
particle interaction data is based on ACE format cross sections, also used
in the MCNP and Serpent Monte Carlo codes.
OpenMC was originally developed by members of the `Computational Reactor Physics
Group`_ at the `Massachusetts Institute of Technology`_ starting
in 2011. Various universities, laboratories, and other organizations now
contribute to the development of OpenMC. For more information on OpenMC, feel
free to send a message to the User's Group `mailing list`_.
free to send a message to the User's Group `mailing list`_. Documentation for
the latest developmental version of the develop branch can be found on
`Read the Docs`_.
.. _Computational Reactor Physics Group: http://crpg.mit.edu
.. _Massachusetts Institute of Technology: http://web.mit.edu
.. _mailing list: https://groups.google.com/forum/?fromgroups=#!forum/openmc-users
.. _Read the Docs: http://openmc.readthedocs.io/en/latest/
.. only:: html
@ -33,6 +37,7 @@ free to send a message to the User's Group `mailing list`_.
usersguide/index
devguide/index
pythonapi/index
io_formats/index
publications
license
developers

102
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@ -0,0 +1,102 @@
.. _io_data_wmp:
=================================
Windowed Multipole Library Format
=================================
**/version** (*char[]*)
The format version of the file. The current version is "v0.2"
**/nuclide/**
- **broaden_poly** (*int[]*)
If 1, Doppler broaden curve fit for window with corresponding index.
If 0, do not.
- **curvefit** (*double[][][]*)
Curve fit coefficients. Indexed by (reaction type, coefficient index,
window index).
- **data** (*complex[][]*)
Complex poles and residues. Each pole has a corresponding set of
residues. For example, the :math:`i`-th pole and corresponding residues
are stored as
.. math::
\text{data}[:,i] = [\text{pole},~\text{residue}_1,~\text{residue}_2,
~\ldots]
The residues are in the order: total, competitive if present,
absorption, fission. Complex numbers are stored by forming a type with
":math:`r`" and ":math:`i`" identifiers, similar to how `h5py`_ does it.
- **end_E** (*double*)
Highest energy the windowed multipole part of the library is valid for.
- **energy_points** (*double[]*)
Energy grid for the pointwise library in the reaction group.
- **fissionable** (*int*)
1 if this nuclide has fission data. 0 if it does not.
- **fit_order** (*int*)
The order of the curve fit.
- **formalism** (*int*)
The formalism of the underlying data. Uses the `ENDF-6`_ format
formalism numbers.
.. table:: Table of supported formalisms.
+-------------+------------------+
| Formalism | Formalism number |
+=============+==================+
| MLBW | 2 |
+-------------+------------------+
| Reich-Moore | 3 |
+-------------+------------------+
- **l_value** (*int[]*)
The index for a corresponding pole. Equivalent to the :math:`l` quantum
number of the resonance the pole comes from :math:`+1`.
- **length** (*int*)
Total count of poles in `data`.
- **max_w** (*int*)
Maximum number of poles in a window.
- **MT_count** (*int*)
Number of pointwise tables in the library.
- **MT_list** (*int[]*)
A list of available MT identifiers. See `ENDF-6`_ for meaning.
- **n_grid** (*int*)
Total length of the pointwise data.
- **num_l** (*int*)
Number of possible :math:`l` quantum states for this nuclide.
- **pseudo_K0RS** (*double[]*)
:math:`l` dependent value of
.. math::
\sqrt{\frac{2 m_n}{\hbar}}\frac{AWR}{AWR + 1} r_{s,l}
Where :math:`m_n` is mass of neutron, :math:`AWR` is the atomic weight
ratio of the target to the neutron, and :math:`r_{s,l}` is the
scattering radius for a given :math:`l`.
- **spacing** (*double*)
.. math::
\frac{\sqrt{E_{max}}- \sqrt{E_{min}}}{n_w}
Where :math:`E_{max}` is the maximum energy the windows go up to. This
is not equivalent to the maximum energy for which the windowed multipole
data is valid for. It is slightly higher to ensure an integer number of
windows. :math:`E_{min}` is the minimum energy and equivalent to
``start_E``, and :math:`n_w` is the number of windows, given by
``windows``.
- **sqrtAWR** (*double*)
Square root of the atomic weight ratio.
- **start_E** (*double*)
Lowest energy the windowed multipole part of the library is valid for.
- **w_start** (*int[]*)
The pole to start from for each window.
- **w_end** (*int[]*)
The pole to end at for each window.
- **windows** (*int*)
Number of windows.
**/nuclide/reactions/MT<i>**
- **MT_sigma** (*double[]*) -- Cross section value for this reaction.
- **Q_value** (*double*) -- Energy released in this reaction, in eV.
- **threshold** (*int*) -- The first non-zero entry in ``MT_sigma``.
.. _h5py: http://docs.h5py.org/en/latest/
.. _ENDF-6: https://www.oecd-nea.org/dbdata/data/manual-endf/endf102.pdf

18
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@ -0,0 +1,18 @@
.. _io_file_formats:
==========================
File Format Specifications
==========================
.. toctree::
:numbered:
:maxdepth: 3
data_wmp
mgxs_library
statepoint
source
summary
particle_restart
track
voxel

304
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@ -0,0 +1,304 @@
.. _io_mgxs_library:
========================================
Multi-Group Cross Section Library Format
========================================
OpenMC can be run in continuous-energy mode or multi-group mode, provided the
nuclear data is available. In continuous-energy mode, the
``cross_sections.xml`` file contains necessary meta-data for each data set,
including the name and a file system location where the complete library
can be found. In multi-group mode, this ``mgxs.xml`` file contains
this same meta-data describing the nuclide or material, but also contains the
group-wise nuclear data. This portion of the manual describes the format of
the multi-group data library required to be used in the ``mgxs.xml``
file.
Similar to the other input file types, the multi-group library is provided in
the XML_ format. This library must provide some meta-data about the library
itself (such as the number of groups and the group structure, etc.) as well as
the actual cross section data itself for each of the necessary nuclides or
materials.
.. _XML: http://www.w3.org/XML/
.. _mgxs_lib_spec:
--------------------------
MGXS Library Specification
--------------------------
The multi-group library meta-data is contained within the groups_,
group_structure_, and inverse_velocities_ elements.
The actual multi-group data itself is contained within the xsdata_ element.
.. _groups:
``<groups>`` Element
--------------------
The ``<groups>`` element has no attributes and simply provides the number of
energy groups contained within the library.
*Default*: None, this must be provided.
.. _group_structure:
``<group_structure>`` Element
-----------------------------
The ``<group_structure>`` element has no attributes and should be provided as a
monotonically increasing list of bounding energies, in MeV, for a number of
groups. To provide proper energy boundaries, the length of the data within the
``<group_structure>`` element should be one more than the number of groups in
the problem. For example, a two-group problem could be specified as:
.. code-block:: xml
<group_structure> 0.0 0.625E-6 20.0 </group_structure>
*Default*: None, this must be provided.
.. _inverse_velocities:
``<inverse_velocities>`` Element
--------------------------------
The ``<inverse_velocities>`` element optionally indicates the average
inverse velocity corresponding to each of the groups in the problem.
This element should therefore be an array with a length which matches the
number of groups set in the groups_ element.
*Default*: Should this be needed by the presence of an ``inverse-velocity``
score in the ``tallies.xml`` file and not provided in this element, OpenMC
will simply convert the group mid-point energy to an inverse of the velocity
and use this information for tallying.
.. _xsdata:
``<xsdata>`` Element
--------------------
The ``<xsdata>`` element contains the nuclide or material-specific meta-data as
well as the actual cross section data. The following are the
attributes/sub-elements required to describe the meta-data:
:name:
The name of the microscopic or macroscopic data set. An extension to the
name must be provided (e.g., the ``.300K`` in ``UO2.300K``). The name and
extension together must be twelve or less characters in length. This
extension must follow a period and be five characters or less in length.
similar to the equivalent in the continuous-energy ``cross_sections.xml``
file, is used to denote variants of the particular nuclide or material of
interest (i.e. the ``UO2`` data in this example could have been generated
at a temperature of 300K).
*Default*: None, this must be provided.
:alias:
An alternative name to use for the microscopic or macroscopic data set.
*Default*: If no alias is provided, it will adopt the value of ``name``.
:kT:
The temperature times Boltzmann's constant (in units of MeV) at which the
data was generated.
*Default*: Room temperature, 2.53E-8 MeV
:fissionable:
This element states whether or not the data in question is fissionable.
Accepted values are "true" or "false".
*Default*: None, this element must be provided.
:representation:
This element provides the method used to generate and represent the
multi-group cross sections. That is, whether they were generated with
scalar flux weighting (or reduced to an equivalent representation)
and thus are angle-independent, or if the data was generated with angular
dependent fluxes and thus the data is angle-dependent. The options are
either "isotropic" or "angle".
*Default*: "isotropic"
:num_azimuthal:
This element provides the number of equal width angular bins that the
azimuthal angular domain is subdivided in the case of angle-dependent
cross sections (i.e., "angle" is passed to the ``representation`` element).
Note that these bins are equal in azimuthal angle widths, not equal in the
cosine of the azimuthal angle widths.
*Default*: If ``representation`` is "angle", this must be provided. This
parameter is not used for other ``representation`` types.
:num_polar:
This element provides the number of equal width angular bins that the
polar angular domain is subdivided in the case of angle-dependent
cross sections (i.e., "angle" is passed to the ``representation`` element).
Note that these bins are equal in polar angle widths, not equal in the
cosine of the polar angle widths.
*Default*: If ``representation`` is "angle", this must be provided. This
parameter is not used for other ``representation`` types.
:scatt_type:
This element provides the representation of the angular distribution
associated with each group-to-group transfer probability. The options are
either "legendre", "histogram", or "tabular".
The "legendre" option means the angular distribution has been
expanded via Legendre polynomials of the order provided in the "order"
element.
The "histogram" option means the angular distribution is provided in
an equi-width histogram format with a number of bins as provided in the
"order" element. This is useful when the angular distribution was
obtained from a Monte Carlo tally and thus is natively in the histogram
format.
The "tabular" option means the angular distribution is provided in an
equi-spaced point-wise representation.
*Default*: "legendre"
:order:
This element provides either the Legendre order, number of bins, or number
of points used to describe the angular distribution associated with each
group-to-group transfer probability. The specific meaning of this bin
depends upon the value of ``scatt_type`` as discussed above.
*Default*: None, this element must be provided.
:tabular_legendre:
This optional element is used to set how the Legendre scattering kernel, if
provided via the ``scatt_type`` element above, is represented and thus used
during the scattering process. Specifically, the options are to either
convert the Legendre expansion to a tabular representation or leave it as
a set of Legendre coefficients. Converting to a tabular representation
will cost memory but can allow for a decrease in runtime compared to
leaving as a set of Legendre coefficients. This element has the following
attributes/sub-elements:
:enable:
This attribute/sub-element denotes whether or not the conversion to the
tabular format should be performed or not. A value of "true" means
the conversion should be performed, "false" means it should not.
*Default*: "true"
:num_points:
If the conversion is to take place the number of tabular points is
required. This attribute/sub-element allows the user to set the desired
number of points.
*Default*: 33
The following attributes/sub-elements are the cross section values to
be used during the transport process.
:total:
This element requires the group-wise total cross section ordered by
increasing group index (i.e., fast to thermal). If ``representation`` is
"isotropic", then the length of this list should equal the number of
groups described in the ``groups`` element. If ``representation`` is
"angle", then the length of this list should equal the number of groups
times the number of azimuthal angles times the number of polar angles,
with the inner-dimension being groups, intermediate-dimension being
azimuthal angles and outer-dimension being the polar angles.
*Default*: If not provided, it will be determined by summing the
absorption and scattering cross sections.
:absorption:
This element requires the group-wise absorption cross section ordered by
increasing group index (i.e., fast to thermal). If ``representation`` is
"isotropic", then the length of this list should equal the number of
groups described in the ``groups`` element. If ``representation`` is
"angle", then the length of this list should equal the number of groups
times the number of azimuthal angles times the number of polar angles,
with the inner-dimension being groups, intermediate-dimension being
azimuthal angles and outer-dimension being the polar angles.
*Default*: None, this must be provided.
:scatter:
This element requires the scattering moment matrices presented with the
columns representing incoming group and rows representing the outgoing
group. That is, down-scatter will be above the diagonal of the resultant
matrix. This matrix is repeated for every Legendre order (in order of
increasing orders) if ``scatt_type`` is "legendre"; otherwise, this
matrix is repeated for every bin of the histogram or tabular
representation. Finally, if ``representation`` is "angle", the above
is repeated for every azimuthal angle and every polar angle, in that
order.
*Default*: None, this must be provided.
:multiplicity:
This element provides the ratio of neutrons produced in scattering
collisions to the neutrons which undergo scattering collisions; that is,
the multiplicity provides the code with a scaling factor to account for
neutrons being produced in (n,xn) reactions. This information is assumed
isotropic and therefore does not need to be repeated for every Legendre
moment or histogram/tabular bin. This matrix follows the same arrangement
as described for the ``scatter`` element, with the exception of the
data needed to provide the scattering type information.
*Default*: Multiplicities of 1.0 are assumed (i.e., (n,xn) reactions are
neglected).
The following fission-specific data are only needed should ``fissionable``
be "true".
:fission:
This element requires the group-wise fission cross section ordered by
increasing group index (i.e., fast to thermal). If ``representation`` is
"isotropic", then the length of this list should equal the number of
groups described in the ``groups`` element. If ``representation`` is
"angle", then the length of this list should equal the number of groups
times the number of azimuthal angles times the number of polar angles,
with the inner-dimension being groups, intermediate-dimension being
azimuthal angles and outer-dimension being the polar angles.
*Default*: None, this is required only if fission tallies are
requested and the material is fissionable.
:kappa_fission:
This element requires the group-wise kappa-fission cross section ordered by
increasing group index (i.e., fast to thermal). If ``representation`` is
"isotropic", then the length of this list should equal the number of
groups described in the ``groups`` element. If ``representation`` is
"angle", then the length of this list should equal the number of groups
times the number of azimuthal angles times the number of polar angles,
with the inner-dimension being groups, intermediate-dimension being
azimuthal angles and outer-dimension being the polar angles.
*Default*: None, this is required only if kappa_fission tallies are
requested and the material is fissionable.
:chi:
This element requires the group-wise fission spectra ordered by
increasing group index (i.e., fast to thermal). This element should be
used if making the common approximation that the fission spectra does
not depend on incoming energy. If the user does not wish to make this
approximation, then this should not be provided and this information
included in the ``nu_fission`` element instead. If ``representation`` is
"isotropic", then the length of this list should equal the number of
groups described in the ``groups`` element. If ``representation`` is
"angle", then the length of this list should equal the number of groups
times the number of azimuthal angles times the number of polar angles,
with the inner-dimension being groups, intermediate-dimension being
azimuthal angles and outer-dimension being the polar angles.
*Default*: None, either this element is provided or ``nu_fission`` is
provided in fission matrix form, or the material is not fissionable.
:nu_fission:
This element provides either the group-wise fission production cross
section vector (i.e., if ``chi`` is provided), or is the group-wise fission
production matrix. If providing the vector, it should be ordered the same
as the ``fission`` data. If providing the matrix, it should be ordered
the same as the ``multiplicity`` matrix.
*Default*: None, either this element must be provided if the material
is fissionable.

5
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@ -1,4 +1,4 @@
.. _usersguide_particle_restart:
.. _io_particle_restart:
============================
Particle Restart File Format
@ -46,7 +46,8 @@ The current revision of the particle restart file format is 1.
**/energy** (*double*)
Energy of the particle in MeV.
Energy of the particle in MeV for continuous-energy mode, or the energy
group of the particle for multi-group mode.
**/xyz** (*double[3]*)

7
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@ -1,4 +1,4 @@
.. _usersguide_source:
.. _io_source:
==================
Source File Format
@ -15,5 +15,6 @@ is that documented here.
**/source_bank** (Compound type)
Source bank information for each particle. The compound type has fields
``wgt``, ``xyz``, ``uvw``, and ``E`` which represent the weight, position,
direction, and energy of the source particle, respectively.
``wgt``, ``xyz``, ``uvw``, ``E``, and ``delayed_group``, which
represent the weight, position, direction, energy, energy group, and
delayed_group of the source particle, respectively.

87
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@ -1,10 +1,10 @@
.. _usersguide_statepoint:
.. _io_statepoint:
=======================
State Point File Format
=======================
The current revision of the statepoint file format is 14.
The current revision of the statepoint file format is 15.
**/filetype** (*char[]*)
@ -39,6 +39,12 @@ The current revision of the statepoint file format is 14.
Pseudo-random number generator seed.
**/run_CE** (*int*)
Flag to denote continuous-energy or multi-group mode. A value of 1
indicates a continuous-energy run while a value of 0 indicates a
multi-group run.
**/run_mode** (*char[]*)
Run mode used. A value of 1 indicates a fixed-source run and a value of 2
@ -185,10 +191,6 @@ if run_mode == 'k-eigenvalue':
Type of the j-th filter. Can be 'universe', 'material', 'cell', 'cellborn',
'surface', 'mesh', 'energy', 'energyout', or 'distribcell'.
**/tallies/tally <uid>/filter <j>/offset** (*int*)
Filter offset (used for distribcell filter).
**/tallies/tally <uid>/filter <j>/n_bins** (*int*)
Number of bins for the j-th filter.
@ -246,7 +248,7 @@ if run_mode == 'k-eigenvalue':
Accumulated sum and sum-of-squares for each global tally. The compound type
has fields named ``sum`` and ``sum_sq``.
**tallies_present** (*int*)
**/tallies_present** (*int*)
Flag indicated if tallies are present in the file.
@ -255,5 +257,72 @@ if (run_mode == 'k-eigenvalue' and source_present > 0)
**/source_bank** (Compound type)
Source bank information for each particle. The compound type has fields
``wgt``, ``xyz``, ``uvw``, and ``E`` which represent the weight,
position, direction, and energy of the source particle, respectively.
``wgt``, ``xyz``, ``uvw``, ``E``, ``g``, and ``delayed_group``, which
represent the weight, position, direction, energy, energy group, and
delayed_group of the source particle, respectively.
**/runtime/total initialization** (*double*)
Time (in seconds on the master process) spent reading inputs, allocating
arrays, etc.
**/runtime/reading cross sections** (*double*)
Time (in seconds on the master process) spent loading cross section
libraries (this is a subset of initialization).
**/runtime/simulation** (*double*)
Time (in seconds on the master process) spent between initialization and
finalization.
**/runtime/transport** (*double*)
Time (in seconds on the master process) spent transporting particles.
**/runtime/inactive batches** (*double*)
Time (in seconds on the master process) spent in the inactive batches
(including non-transport activities like communcating sites).
**/runtime/active batches** (*double*)
Time (in seconds on the master process) spent in the active batches
(including non-transport activities like communicating sites).
**/runtime/synchronizing fission bank** (*double*)
Time (in seconds on the master process) spent sampling source particles
from fission sites and communicating them to other processes for load
balancing.
**/runtime/sampling source sites** (*double*)
Time (in seconds on the master process) spent sampling source particles
from fission sites.
**/runtime/SEND-RECV source sites** (*double*)
Time (in seconds on the master process) spent communicating source sites
between processes for load balancing.
**/runtime/accumulating tallies** (*double*)
Time (in seconds on the master process) spent communicating tally results
and evaluating their statistics.
**/runtime/CMFD** (*double*)
Time (in seconds on the master process) spent evaluating CMFD.
**/runtime/CMFD building matrices** (*double*)
Time (in seconds on the master process) spent buliding CMFD matrices.
**/runtime/CMFD solving matrices** (*double*)
Time (in seconds on the master process) spent solving CMFD matrices.
**/runtime/total** (*double*)
Total time spent (in seconds on the master process) in the program.

30
docs/source/usersguide/output/summary.rst → docs/source/io_formats/summary.rst
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@ -1,4 +1,4 @@
.. _usersguide_summary:
.. _io_summary:
===================
Summary File Format
@ -91,10 +91,16 @@ The current revision of the summary file format is 1.
Type of fill for the cell. Can be 'normal', 'universe', or 'lattice'.
**/geometry/cells/cell <uid>/material** (*int*)
**/geometry/cells/cell <uid>/material** (*int* or *int[]*)
Unique ID of the material assigned to the cell. This dataset is present only
if fill_type is set to 'normal'.
Unique ID of the material(s) assigned to the cell. This dataset is present
only if fill_type is set to 'normal'. The value '-1' signifies void
material. The data is an array if the cell uses distributed materials,
otherwise it is a scalar.
**/geometry/cells/cell <uid>/temperature** (*double[]*)
Temperature of the cell in Kelvin.
**/geometry/cells/cell <uid>/offset** (*int[]*)
@ -121,6 +127,10 @@ The current revision of the summary file format is 1.
Region specification for the cell.
**/geometry/cells/cell <uid>/distribcell_index** (*int*)
Index of this cell in distribcell filter arrays.
**/geometry/surfaces/surface <uid>/index** (*int*)
Index in surfaces array used internally in OpenMC.
@ -287,6 +297,13 @@ The current revision of the summary file format is 1.
Filter offset (used for distribcell filter).
**/tallies/tally <uid>/filter <j>/paths** (*char[][]*)
The paths traversed through the CSG tree to reach each distribcell
instance (for 'distribcell' filters only). This consists of the integer
IDs for each universe, cell and lattice delimited by '->'. Each lattice
cell is specified by its (x,y) or (x,y,z) indices.
**/tallies/tally <uid>/filter <j>/n_bins** (*int*)
Number of bins for the j-th filter.
@ -306,6 +323,11 @@ The current revision of the summary file format is 1.
than the number of user-specified scores since each score might have
multiple scoring bins, e.g., scatter-PN.
**/tallies/tally <uid>/moment_orders** (*char[][]*)
Tallying moment orders for Legendre and spherical harmonic tally expansions
(*e.g.*, 'P2', 'Y1,2', etc.).
**/tallies/tally <uid>/score_bins** (*char[][]*)
Scoring bins for the tally.

2
docs/source/usersguide/output/track.rst → docs/source/io_formats/track.rst
View file

@ -1,4 +1,4 @@
.. _usersguide_track:
.. _io_track:
=================
Track File Format

2
docs/source/usersguide/output/voxel.rst → docs/source/io_formats/voxel.rst
View file

@ -1,4 +1,4 @@
.. _usersguide_voxel:
.. _io_voxel:
======================
Voxel Plot File Format

2
docs/source/license.rst
View file

@ -4,7 +4,7 @@
License Agreement
=================
Copyright © 2011-2015 Massachusetts Institute of Technology
Copyright © 2011-2016 Massachusetts Institute of Technology
Permission is hereby granted, free of charge, to any person obtaining a copy of
this software and associated documentation files (the "Software"), to deal in

22
docs/source/methods/cmfd.rst
View file

@ -8,6 +8,10 @@ This page section discusses how nonlinear diffusion acceleration (NDA) using
coarse mesh finite difference (CMFD) is implemented into OpenMC. Before we get
into the theory, general notation for this section is discussed.
Note that the methods discussed in this section are written specifically for
continuous-energy mode but equivalent apply to the multi-group mode if the
particle's energy is replaced with the particle's group
--------
Notation
--------
@ -110,10 +114,12 @@ illustrated as a flow chart below. After a batch of neutrons
is simulated, NDA can take place. Each of the steps described above is described
in detail in the following sections.
.. tikz:: Flow chart of NDA process. Note "XS" is used for cross section and
"DC" is used for diffusion coefficient.
:libs: shapes, snakes, shadows, arrows, calc, decorations.markings, patterns, fit, matrix, spy
:include: cmfd_tikz/cmfd_flow.tikz
.. figure:: ../_images/cmfd_flow.png
:align: center
:figclass: align-center
Flow chart of NDA process. Note "XS" is used for cross section and "DC" is
used for diffusion coefficient.
Calculation of Macroscopic Cross Sections
-----------------------------------------
@ -422,9 +428,11 @@ during the MC simulation with incoming and outgoing partial currents. This
allows the user to not have to worry about neutrons producing adequate tallies
in mesh cells far away from the core.
.. tikz:: Diagram of CMFD acceleration mesh
:libs: shapes, snakes, shadows, arrows, calc, decorations.markings, patterns, fit, matrix, spy
:include: cmfd_tikz/meshfig.tikz
.. figure:: ../_images/meshfig.png
:align: center
:figclass: align-center
Diagram of CMFD acceleration mesh
During an MC simulation, CMFD tallies are accumulated. The basic tallies needed
are listed in Table :ref:`tab_tally`. Each tally is performed on a spatial and

204
docs/source/methods/cross_sections.rst
View file

@ -1,16 +1,20 @@
.. _methods_cross_sections:
============================
Cross Section Representation
============================
=============================
Cross Section Representations
=============================
The data governing the interaction of neutrons with various nuclei are
represented using the ACE format which is used by MCNP_ and Serpent_. ACE-format
data can be generated with the NJOY_ nuclear data processing system which
converts raw `ENDF/B data`_ into linearly-interpolable data as required by most
Monte Carlo codes. The use of a standard cross section format allows for a
direct comparison of OpenMC with other codes since the same cross section
libraries can be used.
----------------------
Continuous-Energy Data
----------------------
The data governing the interaction of neutrons with
various nuclei for continous-energy problems are represented using the ACE
format which is used by MCNP_ and Serpent_. ACE-format data can be generated
with the NJOY_ nuclear data processing system which converts raw
`ENDF/B data`_ into linearly-interpolable data as required by most Monte Carlo
codes. The use of a standard cross section format allows for a direct comparison
of OpenMC with other codes since the same cross section libraries can be used.
The ACE format contains continuous-energy cross sections for the following types
of reactions: elastic scattering, fission (or first-chance fission,
@ -24,7 +28,6 @@ accurate treatment of self-shielding in the unresolved resonance range. For
bound scatterers, separate tables with :math:`S(\alpha,\beta,T)` scattering law
data can be used.
-------------------
Energy Grid Methods
-------------------
@ -48,7 +51,7 @@ implement a method of reducing the number of energy grid searches in order to
speed up the calculation.
Logarithmic Mapping
-------------------
+++++++++++++++++++
To speed up energy grid searches, OpenMC uses logarithmic mapping technique
[Brown]_ to limit the range of energies that must be searched for each
@ -58,11 +61,177 @@ the nuclide energy grids. By default, OpenMC uses 8000 equal-lethargy segments
as recommended by Brown.
Other Methods
-------------
+++++++++++++
A good survey of other energy grid techniques, including unionized energy grids,
can be found in a paper by Leppanen_.
Windowed Multipole Representation
---------------------------------
In addition to the usual pointwise representation of cross sections, OpenMC
offers support for an experimental data format called windowed multipole (WMP).
This data format requires less memory than pointwise cross sections, and it
allows on-the-fly Doppler broadening to arbitrary temperature.
The multipole method was introduced by [Hwang]_ and the faster windowed
multipole method by [Josey]_. In the multipole format, cross section resonances
are represented by poles, :math:`p_j`, and residues, :math:`r_j`, in the complex
plane. The 0K cross sections in the resolved resonance region can be computed
by summing up a contribution from each pole:
.. math::
\sigma(E, T=0\text{K}) = \frac{1}{E} \sum_j \text{Re} \left[
\frac{i r_j}{\sqrt{E} - p_j} \right]
Assuming free-gas thermal motion, cross sections in the multipole form can be
analytically Doppler broadened to give the form:
.. math::
\sigma(E, T) = \frac{1}{2 E \sqrt{\xi}} \sum_j \text{Re} \left[i r_j
\sqrt{\pi} W_i(z) - \frac{r_j}{\sqrt{\pi}} C \left(\frac{p_j}{\sqrt{\xi}},
\frac{u}{2 \sqrt{\xi}}\right)\right]
.. math::
W_i(z) = \frac{i}{\pi} \int_{-\infty}^\infty dt \frac{e^{-t^2}}{z - t}
.. math::
C \left(\frac{p_j}{\sqrt{\xi}},\frac{u}{2 \sqrt{\xi}}\right) =
2p_j \int_0^\infty du' \frac{e^{-(u + u')^2/4\xi}}{p_j^2 - u'^2}
.. math::
z = \frac{\sqrt{E} - p_j}{2 \sqrt{\xi}}
.. math::
\xi = \frac{k_B T}{4 A}
.. math::
u = \sqrt{E}
where :math:`T` is the temperature of the resonant scatterer, :math:`k_B` is the
Boltzmann constant, :math:`A` is the mass of the target nucleus. For
:math:`E \gg k_b T/A`, the :math:`C` integral is approximately zero, simplifying
the cross section to:
.. math::
\sigma(E, T) = \frac{1}{2 E \sqrt{\xi}} \sum_j \text{Re} \left[i r_j
\sqrt{\pi} W_i(z)\right]
The :math:`W_i` integral simplifies down to an analytic form. We define the
Faddeeva function, :math:`W` as:
.. math::
W(z) = e^{-z^2} \text{Erfc}(-iz)
Through this, the integral transforms as follows:
.. math::
\text{Im} (z) > 0 : W_i(z) = W(z)
.. math::
\text{Im} (z) < 0 : W_i(z) = -W(z^*)^*
There are freely available algorithms_ to evaluate the Faddeeva function. For
many nuclides, the Faddeeva function needs to be evaluated thousands of times to
calculate a cross section. To mitigate that computational cost, the WMP method
only evaluates poles within a certain energy "window" around the incident
neutron energy and accounts for the effect of resonances outside that window
with a polynomial fit. This polynomial fit is then broadened exactly. This
exact broadening can make up for the removal of the :math:`C` integral, as
typically at low energies, only curve fits are used.
Note that the implementation of WMP in OpenMC currently assumes that inelastic
scattering does not occur in the resolved resonance region. This is usually,
but not always the case. Future library versions may eliminate this issue.
The data format used by OpenMC to represent windowed multipole data is specified
in :ref:`io_data_wmp`.
----------------
Multi-Group Data
----------------
The data governing the interaction of particles with various nuclei or materials
are represented using a multi-group library format specific to the OpenMC code.
The format is described in the :ref:`mgxs_lib_spec`.
The data itself can be prepared via traditional paths or directly from a
continuous-energy OpenMC calculation by use of the Python API as is shown in the
:ref:`notebook_mgxs_part_iv` example notebook. This multi-group
library consists of meta-data (such as the energy group structure) and multiple
`xsdata` objects which contains the required microscopic or macroscopic
multi-group data.
At a minimum, the library must contain the absorption cross section
(:math:`\sigma_{a,g}`) and a scattering matrix. If the problem is an eigenvalue
problem then all fissionable materials must also contain either
a fission production matrix cross section
(:math:`\nu\sigma_{f,g\rightarrow g'}`), or
both the fission spectrum data (:math:`\chi_{g'}`) and a fission production
cross section (:math:`\nu\sigma_{f,g}`), or, . The library must also contain
the fission cross section (:math:`\sigma_{f,g}`) or the fission energy release
cross section (:math:`\kappa\sigma_{f,g}`) if the associated tallies are
required by the model using the library.
After a scattering collision, the outgoing particle experiences a change in both
energy and angle. The probability of a particle resulting in a given outgoing
energy group (`g'`) given a certain incoming energy group (`g`) is provided
by the scattering matrix data. The angular information can be expressed either
via Legendre expansion of the particle's change-in-angle (:math:`\mu`), a
tabular representation of the probability distribution function of :math:`\mu`,
or a histogram representation of the same PDF. The formats used to
represent these are described in the :ref:`mgxs_lib_spec`.
Unlike the continuous-energy mode, the multi-group mode does not explicitly
track particles produced from scattering multiplication (i.e., :math:`(n,xn)`)
reactions. These are instead accounted for by adjusting the weight of the
particle after the collision such that the correct total weight is maintained.
The weight adjustment factor is optionally provided by the `multiplicity` data
which is required to be provided in the form of a group-wise matrix.
This data is provided as a group-wise matrix since the probability of producing
multiple particles in a scattering reaction depends on both the incoming energy,
`g`, and the sampled outgoing energy, `g'`. This data represents the average
number of particles emitted from a scattering reaction, given a scattering
reaction has occurred:
.. math::
multiplicity_{g \rightarrow g'} = \frac{\nu_{scatter}\sigma_{s,g \rightarrow g'}}{
\sigma_{s,g \rightarrow g'}}
If this scattering multiplication information is not provided in the library
then no weight adjustment will be performed. This is equivalent to neglecting
any additional particles produced in scattering multiplication reactions.
However, this assumption will result in a loss of accuracy since the total
particle population would not be conserved. This reduction in accuracy due to
the loss in particle conservation can be mitigated by reducing the absorption
cross section as needed to maintain particle conservation. This adjustment can
be done when generating the library, or by OpenMC. To have OpenMC perform the
adjustment, the total cross section (:math:`\sigma_{t,g}`) must be provided.
With this information, OpenMC will then adjust the absorption cross section as
follows:
.. math::
\sigma_{a,g} = \sigma_{t,g} - \sum_{g'}\nu_{scatter}\sigma_{s,g \rightarrow g'}
The above method is the same as is usually done with most deterministic solvers.
Note that this method is less accurate than using the scattering multiplication
weight adjustment since simply reducing the absorption cross section does not
include any information about the outgoing energy of the particles produced in
these reactions.
All of the data discussed in this section can be provided to the code
independent of the particle's direction of motion (i.e., isotropic), or the data
can be provided as a tabular distribution of the polar and azimuthal particle
direction angles. The isotropic representation is the most commonly used,
however inaccuracies are to be expected especially near material interfaces
where a material has a very large cross sections relative to the other material
(as can be expected in the resonance range). The angular representation can be
used to minimize this error.
Finally, the above options for representing the physics do not have to be
consistent across the problem. The number of groups and the structure, however,
does have to be consistent across the data sets. That is to say that each
microscopic or macroscopic data set does not have to apply the same scattering
expansion, treatment of multiplicity or angular representation of the cross
sections. This allows flexibility for the model to use highly anisotropic
scattering information in the water while the fuel can be simulated with linear
or even isotropic scattering.
.. only:: html
.. rubric:: References
@ -70,8 +239,17 @@ can be found in a paper by Leppanen_.
.. [Brown] Forrest B. Brown, "New Hash-based Energy Lookup Algorithm for Monte
Carlo codes," LA-UR-14-24530, Los Alamos National Laboratory (2014).
.. [Hwang] R. N. Hwang, "A Rigorous Pole Representation of Multilevel Cross
Sections and Its Practical Application," *Nucl. Sci. Eng.*, **96**,
192-209 (1987).
.. [Josey] Colin Josey, Pablo Ducru, Benoit Forget, and Kord Smith, "Windowed
Multipole for Cross Section Doppler Broadening," *J. Comp. Phys*,
**307**, 715-727 (2016). http://dx.doi.org/10.1016/j.jcp.2015.08.013
.. _MCNP: http://mcnp.lanl.gov
.. _Serpent: http://montecarlo.vtt.fi
.. _NJOY: http://t2.lanl.gov/codes.shtml
.. _ENDF/B data: http://www.nndc.bnl.gov/endf
.. _Leppanen: http://dx.doi.org/10.1016/j.anucene.2009.03.019
.. _algorithms: http://ab-initio.mit.edu/wiki/index.php/Faddeeva_Package

8
docs/source/methods/geometry.rst
View file

@ -84,10 +84,10 @@ to fully define the surface.
| Plane perpendicular | x-plane | :math:`x - x_0 = 0` | :math:`x_0` |
| to :math:`x`-axis | | | |
+----------------------+------------+------------------------------+-------------------------+
| Plane perpendicular | y-plane | :math:`x - x_0 = 0` | :math:`y_0` |
| Plane perpendicular | y-plane | :math:`y - y_0 = 0` | :math:`y_0` |
| to :math:`y`-axis | | | |
+----------------------+------------+------------------------------+-------------------------+
| Plane perpendicular | z-plane | :math:`x - x_0 = 0` | :math:`z_0` |
| Plane perpendicular | z-plane | :math:`z - z_0 = 0` | :math:`z_0` |
| to :math:`z`-axis | | | |
+----------------------+------------+------------------------------+-------------------------+
| Arbitrary plane | plane | :math:`Ax + By + Cz = D` | :math:`A\;B\;C\;D` |
@ -205,7 +205,7 @@ traveling in its current direction, it will not hit the surface. The complete
derivation for different types of surfaces used in OpenMC will be presented in
the following sections.
Since :math:f(x,y,z)` in general is quadratic in :math:`x`, :math:`y`, and
Since :math:`f(x,y,z)` in general is quadratic in :math:`x`, :math:`y`, and
:math:`z`, this implies that :math:`f(x_0 + du_0, y + dv_0, z + dw_0)` is
quadratic in :math:`d`. Thus we expect at most two real solutions to
:eq:`dist-to-boundary-1`. If no solutions to :eq:`dist-to-boundary-1` exist or
@ -437,6 +437,8 @@ where :math:`(x_0, y_0, z_0)` are the coordinates to the lower-left-bottom
corner of the lattice, and :math:`p_0, p_1, p_2` are the pitches along the
:math:`x`, :math:`y`, and :math:`z` axes, respectively.
.. _hexagonal_indexing:
Hexagonal Lattice Indexing
--------------------------

40
docs/source/methods/introduction.rst
View file

@ -8,7 +8,7 @@ The physical process by which a population of particles evolves over time is
governed by a number of `probability distributions`_. For instance, given a
particle traveling through some material, there is a probability distribution
for the distance it will travel until its next collision (an exponential
distribution). Then, when it collides with a nucleus, there is associated
distribution). Then, when it collides with a nucleus, there is an associated
probability of undergoing each possible reaction with that nucleus. While the
behavior of any single particle is unpredictable, the average behavior of a
large population of particles originating from the same source is well defined.
@ -45,15 +45,20 @@ following steps:
- Initialize the pseudorandom number generator.
- Read ACE format cross sections specified in the problem.
- Read the contiuous-energy or multi-group cross section data specified in
the problem.
- If using a special energy grid treatment such as a union energy grid or
lethargy bins, that must be initialized as well.
lethargy bins, that must be initialized as well in a continuous-energy
problem.
- In a multi-group problem, individual nuclide cross section information is
combined to produce material-specific cross section data.
- In a fixed source problem, source sites are sampled from the specified
source. In an eigenvalue problem, source sites are sampled from some initial
source distribution or from a source file. The source sites consist of
coordinates, a direction, and an energy.
source. In an eigenvalue problem, source sites are sampled from some
initial source distribution or from a source file. The source sites
consist of coordinates, a direction, and an energy.
Once initialization is complete, the actual transport simulation can
proceed. The life of a single particle will proceed as follows:
@ -95,6 +100,10 @@ proceed. The life of a single particle will proceed as follows:
P(i) = \frac{\Sigma_{t,i}}{\Sigma_t}.
Note that the above selection of collided nuclide only applies to
continuous-energy simulations as multi-group simulations use nuclide
data which has already been combined in to material-specific data.
8. Once the specific nuclide is sampled, the random samples a reaction for
that nuclide based on the microscopic cross sections. If the microscopic
cross section for some reaction :math:`x` is :math:`\sigma_x` and the total
@ -105,13 +114,20 @@ proceed. The life of a single particle will proceed as follows:
P(x) = \frac{\sigma_x}{\sigma_t}.
Since multi-group simulations use material-specific data, the above is
performed with those material multi-group cross sections (i.e.,
macroscopic cross sections for the material) instead of microscopic
cross sections for the nuclide).
9. If the sampled reaction is elastic or inelastic scattering, the outgoing
energy and angle is sampled from the appropriate distribution. Reactions
of type :math:`(n,xn)` are treated as scattering and the weight of the
particle is increased by the multiplicity of the reaction. The particle
then continues from step 3. If the reaction is absorption or fission, the
particle dies and if necessary, fission sites are created and stored in the
fission bank.
energy and angle is sampled from the appropriate distribution. In
continuous-energy simulation, reactions of type :math:`(n,xn)` are treated
as scattering and any additional particles which may be created are added
to a secondary particle bank to be tracked later. In a multi-group
simulation, this secondary bank is not used but the particle weight is
increased accordingly. The original particle then continues from step 3.
If the reaction is absorption or fission, the particle dies and if
necessary, fission sites are created and stored in the fission bank.
After all particles have been simulated, there are a few final tasks that must
be performed before the run is finished. This include the following:

97
docs/source/methods/physics.rst
View file

@ -4,6 +4,12 @@
Physics
=======
There are limited differences between physics treatments used in the
continuous-energy and multi-group modes. If distinctions are necessary, each
of the following sections will provide an explanation of the differences.
Otherwise, replacing any references of the particle's energy (`E`) with
references to the particle's energy group (`g`) will suffice.
-----------------------------------
Sampling Distance to Next Collision
-----------------------------------
@ -79,6 +85,10 @@ originating from :math:`(n,\gamma)` and other reactions.
Elastic Scattering
------------------
Note that the multi-group mode makes no distinction between elastic or
inelastic scattering reactions. The spceific multi-group scattering
implementation is discussed in the :ref:`multi-group-scatter` section.
Elastic scattering refers to the process by which a neutron scatters off a
nucleus and does not leave it in an excited. It is referred to as "elastic"
because in the center-of-mass system, the neutron does not actually lose
@ -170,6 +180,10 @@ final direction in the lab system.
Inelastic Scattering
--------------------
Note that the multi-group mode makes no distinction between elastic or
inelastic scattering reactions. The spceific multi-group scattering
implementation is discussed in the :ref:`multi-group-scatter` section.
The major algorithms for inelastic scattering were described in previous
sections. First, a scattering cosine is sampled using the algorithms in
:ref:`sample-angle`. Then an outgoing energy is sampled using the algorithms in
@ -186,12 +200,69 @@ secondary photons from nuclear de-excitation are tracked in OpenMC.
:math:`(n,xn)` Reactions
------------------------
Note that the multi-group mode makes no distinction between elastic or
inelastic scattering reactions. The specific multi-group scattering
implementation is discussed in the :ref:`multi-group-scatter` section.
These types of reactions are just treated as inelastic scattering and as such
are subject to the same procedure as described in :ref:`inelastic-scatter`. For
reactions with integral multiplicity, e.g., :math:`(n,2n)`, an appropriate
number of secondary neutrons are created. For reactions that have a multiplicity
given as a function of the incoming neutron energy (which occasionally occurs
for MT=5), the weight of the outgoing neutron is multiplied by the multiplcity.
for MT=5), the weight of the outgoing neutron is multiplied by the multiplicity.
.. _multi-group-scatter:
----------------------
Multi-Group Scattering
----------------------
In multi-group mode, a scattering collision requires that the outgoing energy
group of the simulated particle be selected from a probability distribution,
the change-in-angle selected from a probability distribution according to
the outgoing energy group, and finally the particle's weight adjusted again
according to the outgoing energy group.
The first step in selecting an outgoing energy group for a particle in a given
incoming energy group is to select a random number (:math:`\xi`) between 0 and
1. This number is then compared to the cumulative distribution function
produced from the outgoing group (`g'`) data for the given incoming group (`g`):
.. math::
CDF = \sum_{g'=0}^{h}\Sigma_{s,g \rightarrow g'}
If the scattering data is represented as a Legendre expansion, then the
value of :math:`\Sigma_{s,g \rightarrow g'}` above is the 0th order forthe
given group transfer. If the data is provided as tabular or histogram data, then
:math:`\Sigma_{s,g \rightarrow g'}` is the sum of all bins of data for a given
`g` and `g'` pair.
Now that the outgoing energy is known the change-in-angle, :math:`\mu` can be
determined. If the data is provided as a Legendre expansion, this is done by
rejection sampling of the probability distribution represented by the Legendre
series. For efficiency, the selected values of the PDF (:math:`f(\mu)`) are
chosen to be between 0 and the maximum value of :math:`f(\mu)` in the domain of
-1 to 1. Note that this sampling scheme automatically forces negative values of
the :math:`f(\mu)` probability distribution function to be treated as zero
probabilities.
If the angular data is instead provided as a tabular representation, then the
value of :math:`\mu` is selected as described in the :ref:`angle-tabular`
section with a linear-linear interpolation scheme.
If the angular data is provided as a histogram representation, then
the value of :math:`\mu` is selected in a similar fashion to that described for
the selection of the outgoing energy (since the energy group representation is
simply a histogram representation) except the CDF is composed of the angular
bins and not the energy groups. However, since we are interested in a specific
value of :math:`\mu` instead of a group, then an angle selected from a uniform
distribution within from the chosen angular bin.
The final step in the scattering treatment is to adjust the weight of the
neutron to account for any production of neutrons due to :math:`(n,xn)`
reactions. This data is obtained from the multiplicity data provided in the
multi-group cross section library for the material of interest.
The scaled value will default to 1.0 if no value is provided in the library.
.. _fission:
@ -271,10 +342,19 @@ position of the collision site are stored in an array called the fission
bank. In a subsequent generation, these fission bank sites are used as starting
source sites.
The above description is similar for the multi-group mode except the data are
provided as group-wise data instead of in a continuous-energy format. In this
case, the outgoing energy of the fission neutrons are represented as histograms
by way of either the nu-fission matrix or chi vector.
-----------------------------------------
Secondary Angles and Energy Distributions
-----------------------------------------
Note that this section is specific to continuous-energy mode since the
multi-group scattering process has already been described including the
secondary energy and angle sampling.
For any reactions with secondary neutrons, it is necessary to sample secondary
angle and energy distributions. This includes elastic and inelastic scattering,
fission, and :math:`(n,xn)` reactions. In some cases, the angle and energy
@ -890,6 +970,9 @@ space distribution at all, the :math:`(n,2n)` reaction with H-2.
Transforming a Particle's Coordinates
-------------------------------------
Since all the multi-group data exists in the laboratory frame of reference, this
section does not apply to the multi-group mode.
Once the cosine of the scattering angle :math:`\mu` has been sampled either from
a angle distribution or a correlated angle-energy distribution, we are still
left with the task of transforming the particle's coordinates. If the outgoing
@ -941,6 +1024,9 @@ the post-collision direction is calculated as
Effect of Thermal Motion on Cross Sections
------------------------------------------
Since all the multi-group data should be generated with thermal scattering
treatments already, this section does not apply to the multi-group mode.
When a neutron scatters off of a nucleus, it may often be assumed that the
target nucleus is at rest. However, the target nucleus will have motion
associated with its thermal vibration, even at absolute zero (This is due to the
@ -1272,6 +1358,8 @@ described fully in `Walsh et al.`_
|sab| Tables
------------
Note that |sab| tables are only applicable to continuous-energy transport.
For neutrons with thermal energies, generally less than 4 eV, the kinematics of
scattering can be affected by chemical binding and crystalline effects of the
target molecule. If these effects are not accounted for in a simulation, the
@ -1461,6 +1549,9 @@ actual algorithm utilized to sample the outgoing angle is shown in equation
Unresolved Resonance Region Probability Tables
----------------------------------------------
Note that unresolved resonance treatments are only applicable to
continuous-energy transport.
In the unresolved resonance energy range, resonances may be so closely spaced
that it is not possible for experimental measurements to resolve all
resonances. To properly account for self-shielding in this energy range, OpenMC
@ -1626,7 +1717,7 @@ another.
.. _ENDF-6 Format: http://www-nds.iaea.org/ndspub/documents/endf/endf102/endf102.pdf
.. _Monte Carlo Sampler: https://laws.lanl.gov/vhosts/mcnp.lanl.gov/pdf_files/la-9721_3rdmcsampler.pdf
.. _Monte Carlo Sampler: https://laws.lanl.gov/vhosts/mcnp.lanl.gov/pdf_files/la-9721.pdf
.. _LA-UR-14-27694: http://permalink.lanl.gov/object/tr?what=info:lanl-repo/lareport/LA-UR-14-27694
@ -1636,4 +1727,4 @@ another.
.. _lectures: https://laws.lanl.gov/vhosts/mcnp.lanl.gov/pdf_files/la-ur-05-4983.pdf
.. _MCNP Manual: https://laws.lanl.gov/vhosts/mcnp.lanl.gov/pdf_files/MCNP5_Manual_Volume_I_LA-UR-03-1987.pdf
.. _MCNP Manual: https://laws.lanl.gov/vhosts/mcnp.lanl.gov/pdf_files/la-ur-03-1987.pdf

2
docs/source/methods/random_numbers.rst
View file

@ -70,5 +70,5 @@ the idea is to determine the new multiplicative and additive constants in
Different Sizes and Good Lattice Structures," *Math. Comput.*, **68**, 249
(1999).
.. _Brown: https://laws.lanl.gov/vhosts/mcnp.lanl.gov/pdf_files/anl_rn_arb-strides_1994.pdf
.. _Brown: https://laws.lanl.gov/vhosts/mcnp.lanl.gov/pdf_files/anl-rn-arb-stride.pdf
.. _linear congruential generator: http://en.wikipedia.org/wiki/Linear_congruential_generator

24
docs/source/methods/tallies.rst
View file

@ -4,6 +4,10 @@
Tallies
=======
Note that the methods discussed in this section are written specifically for
continuous-energy mode but equivalent apply to the multi-group mode if the
particle's energy is replaced with the particle's group
------------------
Filters and Scores
------------------
@ -32,8 +36,9 @@ OpenMC: flux, total reaction rate, scattering reaction rate, neutron production
from scattering, higher scattering moments, :math:`(n,xn)` reaction rates,
absorption reaction rate, fission reaction rate, neutron production rate from
fission, and surface currents. The following variables can be used as filters:
universe, material, cell, birth cell, surface, mesh, pre-collision energy, and
post-collision energy.
universe, material, cell, birth cell, surface, mesh, pre-collision energy,
post-collision energy, polar angle, azimuthal angle, and the cosine of the
change-in-angle due to a scattering event.
With filters for pre- and post-collision energy and scoring functions for
scattering and fission production, it is possible to use OpenMC to generate
@ -55,9 +60,9 @@ be scored to for each value of the filter variable. If a particle is in cell
:math:`n`, the mapping would identify what tally/bin combinations specify cell
:math:`n` for the cell filter variable. In this manner, it is not necessary to
check the phase space variables against each tally. Note that this technique
only applies to discrete filter variables and cannot be applied to energy
bins. For energy filters, it is necessary to perform a binary search on the
specified energy grid.
only applies to discrete filter variables and cannot be applied to energy,
angle, or change-in-angle bins. For these filters, it is necessary to perform
a binary search on the specified energy grid.
-----------------------------------------
Volume-Integrated Flux and Reaction Rates
@ -196,8 +201,9 @@ One important fact to take into consideration is that the use of a track-length
estimator precludes us from using any filter that requires knowledge of the
particle's state following a collision because by definition, it will not have
had a collision at every event. Thus, for tallies with outgoing-energy filters
(which require the post-collision energy) or for tallies of scattering moments
(which require the scattering cosine), we must use an analog estimator.
(which require the post-collision energy), scattering change-in-angle filters,
or for tallies of scattering moments (which require the scattering cosine of
the change-in-angle), we must use an analog estimator.
.. TODO: Add description of surface current tallies
@ -430,7 +436,7 @@ analytically. For one degree of freedom, the t-distribution becomes a standard
.. math::
:label: cauchy-cdf
c(x) = \frac{1}{\pi} \arctan x + \frac{1}{2}.
c(x) = \frac{1}{\pi} \arctan x + \frac{1}{2}.
Thus, inverting the cumulative distribution function, we find the :math:`x`
percentile of the standard Cauchy distribution to be
@ -507,6 +513,6 @@ improve the estimate of the percentile.
.. _Cauchy distribution: http://en.wikipedia.org/wiki/Cauchy_distribution
.. _unpublished rational approximation: http://home.online.no/~pjacklam/notes/invnorm/
.. _unpublished rational approximation: https://web.archive.org/web/20150926021742/http://home.online.no/~pjacklam/notes/invnorm/
.. _MC21: http://www.osti.gov/bridge/servlets/purl/903083-HT5p1o/903083.pdf

2
docs/source/publications.rst
View file

@ -28,7 +28,7 @@ Benchmarking
- Khurrum S. Chaudri and Sikander M. Mirza, "Burnup dependent Monte Carlo
neutron physics calculations of IAEA MTR benchmark," *Prog. Nucl. Energy*,
**81**, 43-52 (2015). `<http://dx.doi.org/j.pnucene.2014.12.018>`_
**81**, 43-52 (2015). `<http://dx.doi.org/10.1016/j.pnucene.2014.12.018>`_
- Daniel J. Kelly, Brian N. Aviles, Paul K. Romano, Bryan R. Herman,
Nicholas E. Horelik, and Benoit Forget, "Analysis of select BEAVRS PWR

8
docs/source/pythonapi/ace.rst
View file

@ -1,8 +0,0 @@
.. _pythonapi_ace:
==========
ACE Format
==========
.. automodule:: openmc.ace
:members:

8
docs/source/pythonapi/cmfd.rst
View file

@ -1,8 +0,0 @@
.. _pythonapi_cmfd:
====
CMFD
====
.. automodule:: openmc.cmfd
:members:

8
docs/source/pythonapi/element.rst
View file

@ -1,8 +0,0 @@
.. _pythonapi_element:
=======
Element
=======
.. automodule:: openmc.element
:members:

8
docs/source/pythonapi/energy_groups.rst
View file

@ -1,8 +0,0 @@
.. _pythonapi_energy_groups:
=============
Energy Groups
=============
.. automodule:: openmc.mgxs.groups
:members:

376
docs/source/pythonapi/examples/mgxs-part-i.ipynb
View file

@ -141,13 +141,12 @@
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"import openmc\n",
"import openmc.mgxs as mgxs\n",
"\n",
"%matplotlib inline"
"import openmc.mgxs as mgxs"
]
},
{
@ -202,7 +201,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"With our material, we can now create a `MaterialsFile` object that can be exported to an actual XML file."
"With our material, we can now create a `Materials` object that can be exported to an actual XML file."
]
},
{
@ -213,10 +212,9 @@
},
"outputs": [],
"source": [
"# Instantiate a MaterialsFile, register all Materials, and export to XML\n",
"materials_file = openmc.MaterialsFile()\n",
"# Instantiate a Materials collection and export to XML\n",
"materials_file = openmc.Materials([inf_medium])\n",
"materials_file.default_xs = '71c'\n",
"materials_file.add_material(inf_medium)\n",
"materials_file.export_to_xml()"
]
},
@ -291,7 +289,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"We now must create a geometry that is assigned a root universe, put the geometry into a `GeometryFile` object, and export it to XML."
"We now must create a geometry that is assigned a root universe and export it to XML."
]
},
{
@ -306,12 +304,8 @@
"openmc_geometry = openmc.Geometry()\n",
"openmc_geometry.root_universe = root_universe\n",
"\n",
"# Instantiate a GeometryFile\n",
"geometry_file = openmc.GeometryFile()\n",
"geometry_file.geometry = openmc_geometry\n",
"\n",
"# Export to \"geometry.xml\"\n",
"geometry_file.export_to_xml()"
"openmc_geometry.export_to_xml()"
]
},
{
@ -334,14 +328,17 @@
"inactive = 10\n",
"particles = 2500\n",
"\n",
"# Instantiate a SettingsFile\n",
"settings_file = openmc.SettingsFile()\n",
"# Instantiate a Settings object\n",
"settings_file = openmc.Settings()\n",
"settings_file.batches = batches\n",
"settings_file.inactive = inactive\n",
"settings_file.particles = particles\n",
"settings_file.output = {'tallies': True, 'summary': True}\n",
"settings_file.output = {'tallies': True}\n",
"\n",
"# Create an initial uniform spatial source distribution over fissionable zones\n",
"bounds = [-0.63, -0.63, -0.63, 0.63, 0.63, 0.63]\n",
"settings_file.set_source_space('fission', bounds)\n",
"uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:], only_fissionable=True)\n",
"settings_file.source = openmc.source.Source(space=uniform_dist)\n",
"\n",
"# Export to \"settings.xml\"\n",
"settings_file.export_to_xml()"
@ -375,10 +372,12 @@
"\n",
"* `TotalXS`\n",
"* `TransportXS`\n",
"* `NuTransportXS`\n",
"* `AbsorptionXS`\n",
"* `CaptureXS`\n",
"* `FissionXS`\n",
"* `NuFissionXS`\n",
"* `KappaFissionXS`\n",
"* `ScatterXS`\n",
"* `NuScatterXS`\n",
"* `ScatterMatrixXS`\n",
@ -397,9 +396,9 @@
"outputs": [],
"source": [
"# Instantiate a few different sections\n",
"total = mgxs.TotalXS(domain=cell, domain_type='cell', groups=groups)\n",
"absorption = mgxs.AbsorptionXS(domain=cell, domain_type='cell', groups=groups)\n",
"scattering = mgxs.ScatterXS(domain=cell, domain_type='cell', groups=groups)"
"total = mgxs.TotalXS(domain=cell, groups=groups)\n",
"absorption = mgxs.AbsorptionXS(domain=cell, groups=groups)\n",
"scattering = mgxs.ScatterXS(domain=cell, groups=groups)"
]
},
{
@ -453,7 +452,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"The `Absorption` object includes tracklength tallies for the 'absorption' and 'flux' scores in the 2-group structure in cell 1. Now that each `MGXS` object contains the tallies that it needs, we must add these tallies to a `TalliesFile` object to generate the \"tallies.xml\" input file for OpenMC."
"The `Absorption` object includes tracklength tallies for the 'absorption' and 'flux' scores in the 2-group structure in cell 1. Now that each `MGXS` object contains the tallies that it needs, we must add these tallies to a `Tallies` object to generate the \"tallies.xml\" input file for OpenMC."
]
},
{
@ -464,21 +463,18 @@
},
"outputs": [],
"source": [
"# Instantiate an empty TalliesFile\n",
"tallies_file = openmc.TalliesFile()\n",
"# Instantiate an empty Tallies object\n",
"tallies_file = openmc.Tallies()\n",
"\n",
"# Add total tallies to the tallies file\n",
"for tally in total.tallies.values():\n",
" tallies_file.add_tally(tally)\n",
"tallies_file += total.tallies.values()\n",
"\n",
"# Add absorption tallies to the tallies file\n",
"for tally in absorption.tallies.values():\n",
" tallies_file.add_tally(tally)\n",
"tallies_file += absorption.tallies.values()\n",
"\n",
"# Add scattering tallies to the tallies file\n",
"for tally in scattering.tallies.values():\n",
" tallies_file.add_tally(tally)\n",
" \n",
"tallies_file += scattering.tallies.values()\n",
"\n",
"# Export to \"tallies.xml\"\n",
"tallies_file.export_to_xml()"
]
@ -514,11 +510,11 @@
" 888\n",
" 888\n",
"\n",
" Copyright: 2011-2015 Massachusetts Institute of Technology\n",
" License: http://mit-crpg.github.io/openmc/license.html\n",
" Version: 0.7.0\n",
" Git SHA1: c4b14a5ef87f004528d35cbf33fef3ed15a386ca\n",
" Date/Time: 2015-12-02 09:11:05\n",
" Copyright: 2011-2016 Massachusetts Institute of Technology\n",
" License: http://openmc.readthedocs.io/en/latest/license.html\n",
" Version: 0.7.1\n",
" Git SHA1: 19feb55e6d5e8350398627f39fb55ee8e2e63011\n",
" Date/Time: 2016-05-13 10:19:16\n",
" MPI Processes: 1\n",
"\n",
" ===========================================================================\n",
@ -545,56 +541,56 @@
"\n",
" Bat./Gen. k Average k \n",
" ========= ======== ==================== \n",
" 1/1 1.19804 \n",
" 2/1 1.12945 \n",
" 3/1 1.15573 \n",
" 4/1 1.13929 \n",
" 5/1 1.16300 \n",
" 6/1 1.22117 \n",
" 7/1 1.19012 \n",
" 8/1 1.11299 \n",
" 9/1 1.16066 \n",
" 10/1 1.12566 \n",
" 11/1 1.20854 \n",
" 12/1 1.14691 1.17773 +/- 0.03082\n",
" 13/1 1.17204 1.17583 +/- 0.01789\n",
" 14/1 1.14148 1.16724 +/- 0.01529\n",
" 15/1 1.17272 1.16834 +/- 0.01189\n",
" 16/1 1.18575 1.17124 +/- 0.01014\n",
" 17/1 1.20498 1.17606 +/- 0.00983\n",
" 18/1 1.14754 1.17249 +/- 0.00923\n",
" 19/1 1.18141 1.17348 +/- 0.00820\n",
" 20/1 1.15074 1.17121 +/- 0.00768\n",
" 21/1 1.15914 1.17011 +/- 0.00703\n",
" 22/1 1.14586 1.16809 +/- 0.00673\n",
" 23/1 1.18999 1.16978 +/- 0.00642\n",
" 24/1 1.15101 1.16844 +/- 0.00609\n",
" 25/1 1.13791 1.16640 +/- 0.00602\n",
" 26/1 1.19791 1.16837 +/- 0.00597\n",
" 27/1 1.19818 1.17012 +/- 0.00587\n",
" 28/1 1.14160 1.16854 +/- 0.00576\n",
" 29/1 1.11487 1.16571 +/- 0.00614\n",
" 30/1 1.17538 1.16620 +/- 0.00584\n",
" 31/1 1.20210 1.16791 +/- 0.00581\n",
" 32/1 1.20078 1.16940 +/- 0.00574\n",
" 33/1 1.14624 1.16839 +/- 0.00558\n",
" 34/1 1.14618 1.16747 +/- 0.00542\n",
" 35/1 1.16866 1.16752 +/- 0.00520\n",
" 36/1 1.18565 1.16821 +/- 0.00504\n",
" 37/1 1.16824 1.16821 +/- 0.00485\n",
" 38/1 1.18299 1.16874 +/- 0.00471\n",
" 39/1 1.21418 1.17031 +/- 0.00480\n",
" 40/1 1.11167 1.16835 +/- 0.00504\n",
" 41/1 1.11545 1.16665 +/- 0.00516\n",
" 42/1 1.11114 1.16491 +/- 0.00529\n",
" 43/1 1.14227 1.16423 +/- 0.00517\n",
" 44/1 1.14104 1.16355 +/- 0.00506\n",
" 45/1 1.16756 1.16366 +/- 0.00492\n",
" 46/1 1.13065 1.16274 +/- 0.00487\n",
" 47/1 1.11251 1.16139 +/- 0.00492\n",
" 48/1 1.14731 1.16101 +/- 0.00481\n",
" 49/1 1.16691 1.16117 +/- 0.00469\n",
" 50/1 1.19679 1.16206 +/- 0.00465\n",
" 1/1 1.11184 \n",
" 2/1 1.15820 \n",
" 3/1 1.18468 \n",
" 4/1 1.17492 \n",
" 5/1 1.19645 \n",
" 6/1 1.18436 \n",
" 7/1 1.14070 \n",
" 8/1 1.15150 \n",
" 9/1 1.19202 \n",
" 10/1 1.17677 \n",
" 11/1 1.20272 \n",
" 12/1 1.21366 1.20819 +/- 0.00547\n",
" 13/1 1.15906 1.19181 +/- 0.01668\n",
" 14/1 1.14687 1.18058 +/- 0.01629\n",
" 15/1 1.14570 1.17360 +/- 0.01442\n",
" 16/1 1.13480 1.16713 +/- 0.01343\n",
" 17/1 1.17680 1.16852 +/- 0.01144\n",
" 18/1 1.16866 1.16853 +/- 0.00990\n",
" 19/1 1.19253 1.17120 +/- 0.00913\n",
" 20/1 1.18124 1.17220 +/- 0.00823\n",
" 21/1 1.19206 1.17401 +/- 0.00766\n",
" 22/1 1.17681 1.17424 +/- 0.00700\n",
" 23/1 1.17634 1.17440 +/- 0.00644\n",
" 24/1 1.13659 1.17170 +/- 0.00654\n",
" 25/1 1.17144 1.17169 +/- 0.00609\n",
" 26/1 1.20649 1.17386 +/- 0.00610\n",
" 27/1 1.11238 1.17024 +/- 0.00678\n",
" 28/1 1.18911 1.17129 +/- 0.00647\n",
" 29/1 1.14681 1.17000 +/- 0.00626\n",
" 30/1 1.12152 1.16758 +/- 0.00641\n",
" 31/1 1.12729 1.16566 +/- 0.00639\n",
" 32/1 1.15399 1.16513 +/- 0.00612\n",
" 33/1 1.13547 1.16384 +/- 0.00599\n",
" 34/1 1.17723 1.16440 +/- 0.00576\n",
" 35/1 1.09296 1.16154 +/- 0.00622\n",
" 36/1 1.19621 1.16287 +/- 0.00612\n",
" 37/1 1.12560 1.16149 +/- 0.00605\n",
" 38/1 1.17872 1.16211 +/- 0.00586\n",
" 39/1 1.17721 1.16263 +/- 0.00568\n",
" 40/1 1.13724 1.16178 +/- 0.00555\n",
" 41/1 1.18526 1.16254 +/- 0.00542\n",
" 42/1 1.13779 1.16177 +/- 0.00531\n",
" 43/1 1.15066 1.16143 +/- 0.00516\n",
" 44/1 1.12174 1.16026 +/- 0.00514\n",
" 45/1 1.17479 1.16068 +/- 0.00501\n",
" 46/1 1.14146 1.16014 +/- 0.00489\n",
" 47/1 1.20464 1.16135 +/- 0.00491\n",
" 48/1 1.15119 1.16108 +/- 0.00479\n",
" 49/1 1.17938 1.16155 +/- 0.00468\n",
" 50/1 1.15798 1.16146 +/- 0.00457\n",
" Creating state point statepoint.50.h5...\n",
"\n",
" ===========================================================================\n",
@ -604,27 +600,27 @@
"\n",
" =======================> TIMING STATISTICS <=======================\n",
"\n",
" Total time for initialization = 4.1700E-01 seconds\n",
" Reading cross sections = 8.9000E-02 seconds\n",
" Total time in simulation = 1.4728E+01 seconds\n",
" Time in transport only = 1.4712E+01 seconds\n",
" Time in inactive batches = 1.7890E+00 seconds\n",
" Time in active batches = 1.2939E+01 seconds\n",
" Total time for initialization = 4.2300E-01 seconds\n",
" Reading cross sections = 9.3000E-02 seconds\n",
" Total time in simulation = 1.6549E+01 seconds\n",
" Time in transport only = 1.6535E+01 seconds\n",
" Time in inactive batches = 2.3650E+00 seconds\n",
" Time in active batches = 1.4184E+01 seconds\n",
" Time synchronizing fission bank = 5.0000E-03 seconds\n",
" Sampling source sites = 3.0000E-03 seconds\n",
" SEND/RECV source sites = 2.0000E-03 seconds\n",
" Time accumulating tallies = 1.0000E-03 seconds\n",
" Total time for finalization = 1.0000E-03 seconds\n",
" Total time elapsed = 1.5155E+01 seconds\n",
" Calculation Rate (inactive) = 13974.3 neutrons/second\n",
" Calculation Rate (active) = 7728.57 neutrons/second\n",
" SEND/RECV source sites = 0.0000E+00 seconds\n",
" Time accumulating tallies = 0.0000E+00 seconds\n",
" Total time for finalization = 0.0000E+00 seconds\n",
" Total time elapsed = 1.6981E+01 seconds\n",
" Calculation Rate (inactive) = 10570.8 neutrons/second\n",
" Calculation Rate (active) = 7050.20 neutrons/second\n",
"\n",
" ============================> RESULTS <============================\n",
"\n",
" k-effective (Collision) = 1.16131 +/- 0.00453\n",
" k-effective (Track-length) = 1.16206 +/- 0.00465\n",
" k-effective (Absorption) = 1.16096 +/- 0.00364\n",
" Combined k-effective = 1.16120 +/- 0.00325\n",
" k-effective (Collision) = 1.15984 +/- 0.00411\n",
" k-effective (Track-length) = 1.16146 +/- 0.00457\n",
" k-effective (Absorption) = 1.16177 +/- 0.00380\n",
" Combined k-effective = 1.16105 +/- 0.00364\n",
" Leakage Fraction = 0.00000 +/- 0.00000\n",
"\n"
]
@ -642,8 +638,7 @@
],
"source": [
"# Run OpenMC\n",
"executor = openmc.Executor()\n",
"executor.run_simulation()"
"openmc.run()"
]
},
{
@ -676,20 +671,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"In addition to the statepoint file, our simulation also created a summary file which encapsulates information about the materials and geometry. This is necessary for the `openmc.mgxs` module to properly process the tally data. We first create a `Summary` object and link it with the statepoint."
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# Load the summary file and link it with the statepoint\n",
"su = openmc.Summary('summary.h5')\n",
"sp.link_with_summary(su)"
"In addition to the statepoint file, our simulation also created a summary file which encapsulates information about the materials and geometry. By default, a `Summary` object is automatically linked when a `StatePoint` is loaded. This is necessary for the `openmc.mgxs` module to properly process the tally data."
]
},
{
@ -701,7 +683,7 @@
},
{
"cell_type": "code",
"execution_count": 18,
"execution_count": 17,
"metadata": {
"collapsed": false
},
@ -736,7 +718,7 @@
},
{
"cell_type": "code",
"execution_count": 19,
"execution_count": 18,
"metadata": {
"collapsed": false
},
@ -750,8 +732,8 @@
"\tDomain Type =\tcell\n",
"\tDomain ID =\t1\n",
"\tCross Sections [cm^-1]:\n",
" Group 1 [6.25e-07 - 20.0 MeV]:\t6.81e-01 +/- 1.88e-01%\n",
" Group 2 [0.0 - 6.25e-07 MeV]:\t1.40e+00 +/- 5.91e-01%\n",
" Group 1 [6.25e-07 - 20.0 MeV]:\t6.81e-01 +/- 2.69e-01%\n",
" Group 2 [0.0 - 6.25e-07 MeV]:\t1.40e+00 +/- 5.93e-01%\n",
"\n",
"\n",
"\n"
@ -771,7 +753,7 @@
},
{
"cell_type": "code",
"execution_count": 20,
"execution_count": 19,
"metadata": {
"collapsed": false
},
@ -797,16 +779,16 @@
" <td>1</td>\n",
" <td>1</td>\n",
" <td>total</td>\n",
" <td>0.668323</td>\n",
" <td>0.001264</td>\n",
" <td>0.667787</td>\n",
" <td>0.001802</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>total</td>\n",
" <td>1.293258</td>\n",
" <td>0.007624</td>\n",
" <td>1.292013</td>\n",
" <td>0.007642</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
@ -814,11 +796,11 @@
],
"text/plain": [
" cell group in nuclide mean std. dev.\n",
"1 1 1 total 0.668323 0.001264\n",
"0 1 2 total 1.293258 0.007624"
"1 1 1 total 0.667787 0.001802\n",
"0 1 2 total 1.292013 0.007642"
]
},
"execution_count": 20,
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
@ -837,7 +819,7 @@
},
{
"cell_type": "code",
"execution_count": 21,
"execution_count": 20,
"metadata": {
"collapsed": true
},
@ -855,7 +837,7 @@
},
{
"cell_type": "code",
"execution_count": 22,
"execution_count": 21,
"metadata": {
"collapsed": false
},
@ -882,7 +864,7 @@
},
{
"cell_type": "code",
"execution_count": 23,
"execution_count": 22,
"metadata": {
"collapsed": false
},
@ -896,7 +878,8 @@
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>cell</th>\n",
" <th>energy [MeV]</th>\n",
" <th>energy low [MeV]</th>\n",
" <th>energy high [MeV]</th>\n",
" <th>nuclide</th>\n",
" <th>score</th>\n",
" <th>mean</th>\n",
@ -907,36 +890,38 @@
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>(0.0e+00 - 6.3e-07)</td>\n",
" <td>0.000000e+00</td>\n",
" <td>6.250000e-07</td>\n",
" <td>total</td>\n",
" <td>(((total / flux) - (absorption / flux)) - (sca...</td>\n",
" <td>4.884981e-15</td>\n",
" <td>0.011274</td>\n",
" <td>-3.774758e-15</td>\n",
" <td>0.011292</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1</td>\n",
" <td>(6.3e-07 - 2.0e+01)</td>\n",
" <td>6.250000e-07</td>\n",
" <td>2.000000e+01</td>\n",
" <td>total</td>\n",
" <td>(((total / flux) - (absorption / flux)) - (sca...</td>\n",
" <td>1.221245e-15</td>\n",
" <td>0.001802</td>\n",
" <td>1.443290e-15</td>\n",
" <td>0.002570</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" cell energy [MeV] nuclide \\\n",
"0 1 (0.0e+00 - 6.3e-07) total \n",
"1 1 (6.3e-07 - 2.0e+01) total \n",
" cell energy low [MeV] energy high [MeV] nuclide \\\n",
"0 1 0.00e+00 6.25e-07 total \n",
"1 1 6.25e-07 2.00e+01 total \n",
"\n",
" score mean std. dev. \n",
"0 (((total / flux) - (absorption / flux)) - (sca... 4.884981e-15 0.011274 \n",
"1 (((total / flux) - (absorption / flux)) - (sca... 1.221245e-15 0.001802 "
" score mean std. dev. \n",
"0 (((total / flux) - (absorption / flux)) - (sca... -3.77e-15 1.13e-02 \n",
"1 (((total / flux) - (absorption / flux)) - (sca... 1.44e-15 2.57e-03 "
]
},
"execution_count": 23,
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
@ -958,7 +943,7 @@
},
{
"cell_type": "code",
"execution_count": 24,
"execution_count": 23,
"metadata": {
"collapsed": false
},
@ -972,7 +957,8 @@
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>cell</th>\n",
" <th>energy [MeV]</th>\n",
" <th>energy low [MeV]</th>\n",
" <th>energy high [MeV]</th>\n",
" <th>nuclide</th>\n",
" <th>score</th>\n",
" <th>mean</th>\n",
@ -983,36 +969,38 @@
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>(0.0e+00 - 6.3e-07)</td>\n",
" <td>0.000000e+00</td>\n",
" <td>6.250000e-07</td>\n",
" <td>total</td>\n",
" <td>((absorption / flux) / (total / flux))</td>\n",
" <td>0.076219</td>\n",
" <td>0.000651</td>\n",
" <td>0.076115</td>\n",
" <td>0.000649</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1</td>\n",
" <td>(6.3e-07 - 2.0e+01)</td>\n",
" <td>6.250000e-07</td>\n",
" <td>2.000000e+01</td>\n",
" <td>total</td>\n",
" <td>((absorption / flux) / (total / flux))</td>\n",
" <td>0.019319</td>\n",
" <td>0.000086</td>\n",
" <td>0.019263</td>\n",
" <td>0.000095</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" cell energy [MeV] nuclide score \\\n",
"0 1 (0.0e+00 - 6.3e-07) total ((absorption / flux) / (total / flux)) \n",
"1 1 (6.3e-07 - 2.0e+01) total ((absorption / flux) / (total / flux)) \n",
" cell energy low [MeV] energy high [MeV] nuclide \\\n",
"0 1 0.00e+00 6.25e-07 total \n",
"1 1 6.25e-07 2.00e+01 total \n",
"\n",
" mean std. dev. \n",
"0 0.076219 0.000651 \n",
"1 0.019319 0.000086 "
" score mean std. dev. \n",
"0 ((absorption / flux) / (total / flux)) 7.61e-02 6.49e-04 \n",
"1 ((absorption / flux) / (total / flux)) 1.93e-02 9.46e-05 "
]
},
"execution_count": 24,
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
@ -1027,7 +1015,7 @@
},
{
"cell_type": "code",
"execution_count": 25,
"execution_count": 24,
"metadata": {
"collapsed": false
},
@ -1041,7 +1029,8 @@
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>cell</th>\n",
" <th>energy [MeV]</th>\n",
" <th>energy low [MeV]</th>\n",
" <th>energy high [MeV]</th>\n",
" <th>nuclide</th>\n",
" <th>score</th>\n",
" <th>mean</th>\n",
@ -1052,36 +1041,38 @@
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>(0.0e+00 - 6.3e-07)</td>\n",
" <td>0.000000e+00</td>\n",
" <td>6.250000e-07</td>\n",
" <td>total</td>\n",
" <td>((scatter / flux) / (total / flux))</td>\n",
" <td>0.923781</td>\n",
" <td>0.007714</td>\n",
" <td>0.923885</td>\n",
" <td>0.007736</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1</td>\n",
" <td>(6.3e-07 - 2.0e+01)</td>\n",
" <td>6.250000e-07</td>\n",
" <td>2.000000e+01</td>\n",
" <td>total</td>\n",
" <td>((scatter / flux) / (total / flux))</td>\n",
" <td>0.980681</td>\n",
" <td>0.002617</td>\n",
" <td>0.980737</td>\n",
" <td>0.003737</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" cell energy [MeV] nuclide score \\\n",
"0 1 (0.0e+00 - 6.3e-07) total ((scatter / flux) / (total / flux)) \n",
"1 1 (6.3e-07 - 2.0e+01) total ((scatter / flux) / (total / flux)) \n",
" cell energy low [MeV] energy high [MeV] nuclide \\\n",
"0 1 0.00e+00 6.25e-07 total \n",
"1 1 6.25e-07 2.00e+01 total \n",
"\n",
" mean std. dev. \n",
"0 0.923781 0.007714 \n",
"1 0.980681 0.002617 "
" score mean std. dev. \n",
"0 ((scatter / flux) / (total / flux)) 9.24e-01 7.74e-03 \n",
"1 ((scatter / flux) / (total / flux)) 9.81e-01 3.74e-03 "
]
},
"execution_count": 25,
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
@ -1103,7 +1094,7 @@
},
{
"cell_type": "code",
"execution_count": 26,
"execution_count": 25,
"metadata": {
"collapsed": false
},
@ -1117,7 +1108,8 @@
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>cell</th>\n",
" <th>energy [MeV]</th>\n",
" <th>energy low [MeV]</th>\n",
" <th>energy high [MeV]</th>\n",
" <th>nuclide</th>\n",
" <th>score</th>\n",
" <th>mean</th>\n",
@ -1128,36 +1120,38 @@
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>(0.0e+00 - 6.3e-07)</td>\n",
" <td>0.000000e+00</td>\n",
" <td>6.250000e-07</td>\n",
" <td>total</td>\n",
" <td>(((absorption / flux) / (total / flux)) + ((sc...</td>\n",
" <td>1</td>\n",
" <td>0.007741</td>\n",
" <td>1.0</td>\n",
" <td>0.007763</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1</td>\n",
" <td>(6.3e-07 - 2.0e+01)</td>\n",
" <td>6.250000e-07</td>\n",
" <td>2.000000e+01</td>\n",
" <td>total</td>\n",
" <td>(((absorption / flux) / (total / flux)) + ((sc...</td>\n",
" <td>1</td>\n",
" <td>0.002619</td>\n",
" <td>1.0</td>\n",
" <td>0.003739</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" cell energy [MeV] nuclide \\\n",
"0 1 (0.0e+00 - 6.3e-07) total \n",
"1 1 (6.3e-07 - 2.0e+01) total \n",
" cell energy low [MeV] energy high [MeV] nuclide \\\n",
"0 1 0.00e+00 6.25e-07 total \n",
"1 1 6.25e-07 2.00e+01 total \n",
"\n",
" score mean std. dev. \n",
"0 (((absorption / flux) / (total / flux)) + ((sc... 1 0.007741 \n",
"1 (((absorption / flux) / (total / flux)) + ((sc... 1 0.002619 "
" score mean std. dev. \n",
"0 (((absorption / flux) / (total / flux)) + ((sc... 1.00e+00 7.76e-03 \n",
"1 (((absorption / flux) / (total / flux)) + ((sc... 1.00e+00 3.74e-03 "
]
},
"execution_count": 26,
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}

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.. _notebook_mgxs_part_iv:
====================================================
MGXS Part IV: Multi-Group Mode Cross-Section Library
====================================================
.. only:: html
.. notebook:: mgxs-part-iv.ipynb
.. only:: latex
IPython notebooks must be viewed in the online HTML documentation.

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.. _pythonapi_executor:
========
Executor
========
.. automodule:: openmc.executor
:members:

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.. _pythonapi_filter:
======
Filter
======
.. automodule:: openmc.filter
:members:

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.. _pythonapi_geometry:
========
Geometry
========
.. automodule:: openmc.geometry
:members:

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@ -13,60 +13,9 @@ online. We recommend going through the modules from Codecademy_ and/or the
`Scipy lectures`_. The full API documentation serves to provide more information
on a given module or class.
**Handling nuclear data:**
.. toctree::
:maxdepth: 1
ace
**Creating input files:**
.. toctree::
:maxdepth: 1
cmfd
element
filter
geometry
material
mesh
nuclide
opencg_compatible
plots
settings
surface
tallies
trigger
universe
**Running OpenMC:**
.. toctree::
:maxdepth: 1
executor
**Post-processing:**
.. toctree::
:maxdepth: 1
particle_restart
statepoint
summary
tallies
**Multi-Group Cross Section Generation**
.. toctree::
:maxdepth: 1
mgxs
energy_groups
mgxs_library
**Example Jupyter Notebooks:**
-------------------------
Example Jupyter Notebooks
-------------------------
.. toctree::
:maxdepth: 1
@ -77,6 +26,305 @@ on a given module or class.
examples/mgxs-part-i
examples/mgxs-part-ii
examples/mgxs-part-iii
examples/mgxs-part-iv
------------------------------------
:mod:`openmc` -- Basic Functionality
------------------------------------
Handling nuclear data
---------------------
Classes
+++++++
.. autosummary::
:toctree: generated
:nosignatures:
:template: myclass.rst
openmc.XSdata
openmc.MGXSLibrary
Functions
+++++++++
.. autosummary::
:toctree: generated
:nosignatures:
openmc.ace.ascii_to_binary
Simulation Settings
-------------------
.. autosummary::
:toctree: generated
:nosignatures:
:template: myclass.rst
openmc.Source
openmc.ResonanceScattering
openmc.Settings
Material Specification
----------------------
.. autosummary::
:toctree: generated
:nosignatures:
:template: myclass.rst
openmc.Nuclide
openmc.Element
openmc.Macroscopic
openmc.Material
openmc.Materials
Building geometry
-----------------
.. autosummary::
:toctree: generated
:nosignatures:
:template: myclass.rst
openmc.Plane
openmc.XPlane
openmc.YPlane
openmc.ZPlane
openmc.XCylinder
openmc.YCylinder
openmc.ZCylinder
openmc.Sphere
openmc.Cone
openmc.XCone
openmc.YCone
openmc.ZCone
openmc.Quadric
openmc.Halfspace
openmc.Intersection
openmc.Union
openmc.Complement
openmc.Cell
openmc.Universe
openmc.RectLattice
openmc.HexLattice
openmc.Geometry
Many of the above classes are derived from several abstract classes:
.. autosummary::
:toctree: generated
:nosignatures:
:template: myclass.rst
openmc.Surface
openmc.Region
openmc.Lattice
One function is also available to create a hexagonal region defined by the
intersection of six surface half-spaces.
.. autosummary::
:toctree: generated
:nosignatures:
:template: myfunction.rst
openmc.make_hexagon_region
Constructing Tallies
--------------------
.. autosummary::
:toctree: generated
:nosignatures:
:template: myclass.rst
openmc.Filter
openmc.Mesh
openmc.Trigger
openmc.Tally
openmc.Tallies
Coarse Mesh Finite Difference Acceleration
------------------------------------------
.. autosummary::
:toctree: generated
:nosignatures:
:template: myclass.rst
openmc.CMFDMesh
openmc.CMFD
Plotting
--------
.. autosummary::
:toctree: generated
:nosignatures:
:template: myclass.rst
openmc.Plot
openmc.Plots
Running OpenMC
--------------
.. autosummary::
:toctree: generated
:nosignatures:
:template: myfunction.rst
openmc.run
openmc.plot_geometry
Post-processing
---------------
.. autosummary::
:toctree: generated
:nosignatures:
:template: myclass.rst
openmc.Particle
openmc.StatePoint
openmc.Summary
Various classes may be created when performing tally slicing and/or arithmetic:
.. autosummary::
:toctree: generated
:nosignatures:
:template: myclass.rst
openmc.arithmetic.CrossScore
openmc.arithmetic.CrossNuclide
openmc.arithmetic.CrossFilter
openmc.arithmetic.AggregateScore
openmc.arithmetic.AggregateNuclide
openmc.arithmetic.AggregateFilter
---------------------------------
:mod:`openmc.stats` -- Statistics
---------------------------------
Univariate Probability Distributions
------------------------------------
.. autosummary::
:toctree: generated
:nosignatures:
:template: myclass.rst
openmc.stats.Univariate
openmc.stats.Discrete
openmc.stats.Uniform
openmc.stats.Maxwell
openmc.stats.Watt
openmc.stats.Tabular
Angular Distributions
---------------------
.. autosummary::
:toctree: generated
:nosignatures:
:template: myclass.rst
openmc.stats.UnitSphere
openmc.stats.PolarAzimuthal
openmc.stats.Isotropic
openmc.stats.Monodirectional
Spatial Distributions
---------------------
.. autosummary::
:toctree: generated
:nosignatures:
:template: myclass.rst
openmc.stats.Spatial
openmc.stats.CartesianIndependent
openmc.stats.Box
openmc.stats.Point
----------------------------------------------------------
:mod:`openmc.mgxs` -- Multi-Group Cross Section Generation
----------------------------------------------------------
Energy Groups
-------------
.. autosummary::
:toctree: generated
:nosignatures:
:template: myclass.rst
openmc.mgxs.EnergyGroups
Multi-group Cross Sections
--------------------------
.. autosummary::
:toctree: generated
:nosignatures:
:template: myclassinherit.rst
openmc.mgxs.MGXS
openmc.mgxs.AbsorptionXS
openmc.mgxs.CaptureXS
openmc.mgxs.Chi
openmc.mgxs.FissionXS
openmc.mgxs.KappaFissionXS
openmc.mgxs.MultiplicityMatrixXS
openmc.mgxs.NuFissionXS
openmc.mgxs.NuFissionMatrixXS
openmc.mgxs.NuScatterXS
openmc.mgxs.NuScatterMatrixXS
openmc.mgxs.ScatterXS
openmc.mgxs.ScatterMatrixXS
openmc.mgxs.TotalXS
openmc.mgxs.TransportXS
Multi-group Cross Section Libraries
-----------------------------------
.. autosummary::
:toctree: generated
:nosignatures:
:template: myclass.rst
openmc.mgxs.Library
-------------------------------------
:mod:`openmc.model` -- Model Building
-------------------------------------
TRISO Fuel Modeling
-------------------
Classes
+++++++
.. autosummary::
:toctree: generated
:nosignatures:
:template: myclass.rst
openmc.model.TRISO
Functions
+++++++++
.. autosummary::
:toctree: generated
:nosignatures:
openmc.model.create_triso_lattice
.. _Jupyter: https://jupyter.org/
.. _NumPy: http://www.numpy.org/

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.. _pythonapi_material:
=========
Materials
=========
.. automodule:: openmc.material
:members:

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.. _pythonapi_mesh:
====
Mesh
====
.. automodule:: openmc.mesh
:members:

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@ -1,66 +0,0 @@
.. _pythonapi_mgxs:
==========================
Multi-Group Cross Sections
==========================
.. currentmodule:: openmc.mgxs.mgxs
----------------------------
Summary of Available Classes
----------------------------
.. autosummary::
MGXS
AbsorptionXS
CaptureXS
Chi
FissionXS
NuFissionXS
NuScatterXS
NuScatterMatrixXS
ScatterXS
ScatterMatrixXS
TotalXS
TransportXS
-------------------
Class Documentation
-------------------
.. autoclass:: MGXS
:members:
.. autoclass:: AbsorptionXS
:members:
.. autoclass:: CaptureXS
:members:
.. autoclass:: Chi
:members:
.. autoclass:: FissionXS
:members:
.. autoclass:: NuFissionXS
:members:
.. autoclass:: NuScatterXS
:members:
.. autoclass:: NuScatterMatrixXS
:members:
.. autoclass:: ScatterXS
:members:
.. autoclass:: ScatterMatrixXS
:members:
.. autoclass:: TotalXS
:members:
.. autoclass:: TransportXS
:members:

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.. _pythonapi_mgxs_library:
============
MGXS Library
============
.. automodule:: openmc.mgxs.library
:members:

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@ -1,8 +0,0 @@
.. _pythonapi_nuclide:
=======
Nuclide
=======
.. automodule:: openmc.nuclide
:members:

8
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@ -1,8 +0,0 @@
.. _pythonapi_particle_restart:
================
Particle Restart
================
.. automodule:: openmc.particle_restart
:members:

8
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@ -1,8 +0,0 @@
.. _pythonapi_plots:
=====
Plots
=====
.. automodule:: openmc.plots
:members:

8
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@ -1,8 +0,0 @@
.. _pythonapi_settings:
========
Settings
========
.. automodule:: openmc.settings
:members:

8
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@ -1,8 +0,0 @@
.. _pythonapi_statepoint:
==========
Statepoint
==========
.. automodule:: openmc.statepoint
:members:

8
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@ -1,8 +0,0 @@
.. _pythonapi_summary:
=======
Summary
=======
.. automodule:: openmc.summary
:members:

8
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@ -1,8 +0,0 @@
.. _pythonapi_surface:
=======
Surface
=======
.. automodule:: openmc.surface
:members:

8
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@ -1,8 +0,0 @@
.. _pythonapi_tallies:
=======
Tallies
=======
.. automodule:: openmc.tallies
:members:

8
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@ -1,8 +0,0 @@
.. _pythonapi_trigger:
=======
Trigger
=======
.. automodule:: openmc.trigger
:members:

8
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@ -1,8 +0,0 @@
.. _pythonapi_universe:
========
Universe
========
.. automodule:: openmc.universe
:members:

44
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@ -12,24 +12,55 @@ OpenMC, see :ref:`usersguide_install` in the User's Manual.
Installing on Ubuntu through PPA
--------------------------------
For users with Ubuntu 11.10 or later, a binary package for OpenMC is available
through a `Personal Package Archive`_ (PPA) and can be installed through the `APT
package manager`_. Simply enter the following commands into the terminal:
For users with Ubuntu 15.04 or later, a binary package for OpenMC is available
through a `Personal Package Archive`_ (PPA) and can be installed through the
`APT package manager`_. First, add the following PPA to the repository sources:
.. code-block:: sh
sudo apt-add-repository ppa:paulromano/staging
Next, resynchronize the package index files:
.. code-block:: sh
sudo apt-get update
Now OpenMC should be recognized within the repository and can be installed:
.. code-block:: sh
sudo apt-get install openmc
Currently, the binary package does not allow for parallel simulations or use of
HDF5_. Users who need such capabilities should build OpenMC from source as is
described in :ref:`usersguide_install`.
Binary packages from this PPA may exist for earlier versions of Ubuntu, but they
are no longer supported.
.. _Personal Package Archive: https://launchpad.net/~paulromano/+archive/staging
.. _APT package manager: https://help.ubuntu.com/community/AptGet/Howto
.. _HDF5: http://www.hdfgroup.org/HDF5/
---------------------------------------
Installing from Source on Ubuntu 15.04+
---------------------------------------
To build OpenMC from source, several :ref:`prerequisites <prerequisites>` are
needed. If you are using Ubuntu 15.04 or higher, all prerequisites can be
installed directly from the package manager.
.. code-block:: sh
sudo apt-get install gfortran
sudo apt-get install cmake
sudo apt-get install libhdf5-dev
After the packages have been installed, follow the instructions below for
building and installing OpenMC from source.
.. note:: Before Ubuntu 15.04, the HDF5 package included in the Ubuntu Package
archive was not built with support for the Fortran 2003 HDF5
interface, which is needed by OpenMC. If you are using Ubuntu 14.10 or
before you will need to build HDF5 from source.
-------------------------------------------
Installing from Source on Linux or Mac OS X
-------------------------------------------
@ -42,7 +73,6 @@ entering the following commands in a terminal:
git clone https://github.com/mit-crpg/openmc.git
cd openmc
git checkout -b master origin/master
mkdir build && cd build
cmake ..
make

113
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@ -1,78 +1,83 @@
.. _releasenotes:
==============================
Release Notes for OpenMC 0.7.1
Release Notes for OpenMC 0.8.0
==============================
This release of OpenMC provides some substantial improvements over version
0.7.0. Non-simple cell regions can now be defined through the ``|`` (union) and
``~`` (complement) operators. Similar changes in the Python API also allow
complex cell regions to be defined. A true secondary particle bank now exists;
this is crucial for photon transport (to be added in the next minor release). A
rich API for multi-group cross section generation has been added via the
``openmc.mgxs`` Python module.
This release of OpenMC includes a few new major features including the
capability to perform neutron transport with multi-group cross section data as
well as experimental support for the windowed multipole method being developed
at MIT. Source sampling options have also been expanded significantly, with the
option to supply arbitrary tabular and discrete distributions for energy, angle,
and spatial coordinates.
Various improvements to tallies have also been made. It is now possible to
explicitly specify that a collision estimator be used in a tally. A new
``delayedgroup`` filter and ``delayed-nu-fission`` score allow a user to obtain
delayed fission neutron production rates filtered by delayed group. Finally, the
new ``inverse-velocity`` score may be useful for calculating kinetics
parameters.
The Python API has been significantly restructured in this release compared to
version 0.7.1. Any scripts written based on the version 0.7.1 API will likely
need to be rewritten. Some of the most visible changes include the following:
.. caution:: In previous versions, depending on how OpenMC was compiled binary
output was either given in HDF5 or a flat binary format. With this
version, all binary output is now HDF5 which means you **must**
have HDF5 in order to install OpenMC. Please consult the user's
guide for instructions on how to compile with HDF5.
- ``SettingsFile`` is now ``Settings``, ``MaterialsFile`` is now ``Materials``,
and ``TalliesFile`` is now ``Tallies``.
- The ``GeometryFile`` class no longer exists and is replaced by the
``Geometry`` class which now has an ``export_to_xml()`` method.
- Source distributions are defined using the ``Source`` class and assigned to
the ``Settings.source`` property.
- The ``Executor`` class no longer exists and is replaced by ``openmc.run()``
and ``openmc.plot_geometry()`` functions.
The Python API documentation has also been significantly expanded.
-------------------
System Requirements
-------------------
There are no special requirements for running the OpenMC code. As of this
release, OpenMC has been tested on a variety of Linux distributions, Mac OS X,
and Microsoft Windows 7. Memory requirements will vary depending on the size of
the problem at hand (mostly on the number of nuclides in the problem).
release, OpenMC has been tested on a variety of Linux distributions and Mac
OS X. Numerous users have reported working builds on Microsoft Windows, but your
mileage may vary. Memory requirements will vary depending on the size of the
problem at hand (mostly on the number of nuclides and tallies in the problem).
------------
New Features
------------
- Support for complex cell regions (union and complement operators)
- Generic quadric surface type
- Improved handling of secondary particles
- Binary output is now solely HDF5
- ``openmc.mgxs`` Python module enabling multi-group cross section generation
- Collision estimator for tallies
- Delayed fission neutron production tallies with ability to filter by delayed
group
- Inverse velocity tally score
- Performance improvements for binary search
- Performance improvements for reaction rate tallies
- Multi-group mode
- Vast improvements to the Python API
- Experimental windowed multipole capability
- Periodic boundary conditions
- Expanded source sampling options
- Distributed materials
- Subcritical multiplication support
- Improved method for reproducible URR table sampling
- Refactor of continuous-energy reaction data
- Improved documentation and new Jupyter notebooks
---------
Bug Fixes
---------
- 299322_: Bug with material filter when void material present
- d74840_: Fix triggers on tallies with multiple filters
- c29a81_: Correctly handle maximum transport energy
- 3edc23_: Fixes in the nu-scatter score
- 629e3b_: Assume unspecified surface coefficients are zero in Python API
- 5dbe8b_: Fix energy filters for openmc-plot-mesh-tally
- ff66f4_: Fixes in the openmc-plot-mesh-tally script
- 441fd4_: Fix bug in kappa-fission score
- 7e5974_: Allow fixed source simulations from Python API
- 70daa7_: Make sure MT=3 cross section is not used
- 40b05f_: Ensure source bank is resampled for fixed source runs
- 9586ed_: Fix two hexagonal lattice bugs
- a855e8_: Make sure graphite models don't error out on max events
- 7294a1_: Fix incorrect check on cmfd.xml
- 12f246_: Ensure number of realizations is written to statepoint
- 0227f4_: Fix bug when sampling multiple energy distributions
- 51deaa_: Prevent segfault when user specifies '18' on tally scores
- fed74b_: Prevent duplicate tally scores
- 8467ae_: Better threshold for allowable lost particles
- 493c6f_: Fix type of return argument for h5pget_driver_f
.. _299322: https://github.com/mit-crpg/openmc/commit/299322
.. _d74840: https://github.com/mit-crpg/openmc/commit/d74840
.. _c29a81: https://github.com/mit-crpg/openmc/commit/c29a81
.. _3edc23: https://github.com/mit-crpg/openmc/commit/3edc23
.. _629e3b: https://github.com/mit-crpg/openmc/commit/629e3b
.. _5dbe8b: https://github.com/mit-crpg/openmc/commit/5dbe8b
.. _ff66f4: https://github.com/mit-crpg/openmc/commit/ff66f4
.. _441fd4: https://github.com/mit-crpg/openmc/commit/441fd4
.. _7e5974: https://github.com/mit-crpg/openmc/commit/7e5974
.. _70daa7: https://github.com/mit-crpg/openmc/commit/70daa7
.. _40b05f: https://github.com/mit-crpg/openmc/commit/40b05f
.. _9586ed: https://github.com/mit-crpg/openmc/commit/9586ed
.. _a855e8: https://github.com/mit-crpg/openmc/commit/a855e8
.. _7294a1: https://github.com/mit-crpg/openmc/commit/7294a1
.. _12f246: https://github.com/mit-crpg/openmc/commit/12f246
.. _0227f4: https://github.com/mit-crpg/openmc/commit/0227f4
.. _51deaa: https://github.com/mit-crpg/openmc/commit/51deaa
.. _fed74b: https://github.com/mit-crpg/openmc/commit/fed74b
.. _8467ae: https://github.com/mit-crpg/openmc/commit/8467ae
.. _493c6f: https://github.com/mit-crpg/openmc/commit/493c6f
------------
Contributors
@ -81,11 +86,11 @@ Contributors
This release contains new contributions from the following people:
- `Will Boyd <wbinventor@gmail.com>`_
- `Sterling Harper <sterlingmharper@mit.edu>`_
- `Bryan Herman <hermab53@gmail.com>`_
- `Derek Gaston <friedmud@gmail.com>`_
- `Sterling Harper <sterlingmharper@gmail.com>`_
- `Colin Josey <cjosey@mit.edu>`_
- `Jingang Liang <liangjg2008@gmail.com>`_
- `Adam Nelson <nelsonag@umich.edu>`_
- `Paul Romano <paul.k.romano@gmail.com>`_
- `Kelly Rowland <kellylynnerowland@gmail.com>`_
- `Sam Shaner <samuelshaner@gmail.com>`_
- `Jon Walsh <walshjon@mit.edu>`_

4
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@ -12,7 +12,7 @@ In a nutshell, OpenMC simulates neutrons moving around randomly in a `nuclear
reactor`_ (or other fissile system). This is what's known as `Monte Carlo`_
simulation. Neutrons are important in nuclear reactors because they are the
particles that induce `fission`_ in uranium and other nuclides. Knowing the
behavior of neutrons allows you to figure out how often and where fission
behavior of neutrons allows you to determine how often and where fission
occurs. The amount of energy released is then directly proportional to the
fission reaction rate since most heat is produced by fission. By simulating many
neutrons (millions or billions), it is possible to determine the average
@ -65,7 +65,7 @@ Now let's look at the pros and cons of Monte Carlo methods:
- **Pro**: Running simulations in parallel is conceptually very simple.
- **Con**: Because they related on repeated random sampling, they are
- **Con**: Because they rely on repeated random sampling, they are
computationally very expensive.
- **Con**: A simulation doesn't automatically give you the global solution

1
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@ -14,6 +14,5 @@ essential aspects of using OpenMC to perform simulations.
beginners
install
input
output/index
processing
troubleshoot

630
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View file

@ -112,9 +112,11 @@ standard deviation.
The ``<cross_sections>`` element has no attributes and simply indicates the path
to an XML cross section listing file (usually named cross_sections.xml). If this
element is absent from the settings.xml file, the :envvar:`CROSS_SECTIONS`
environment variable will be used to find the path to the XML cross section
listing.
element is absent from the settings.xml file, the
:envvar:`OPENMC_CROSS_SECTIONS` environment variable will be used to find the
path to the XML cross section listing when in continuous-energy mode, and the
:envvar:`OPENMC_MG_CROSS_SECTIONS` environment variable will be used in
multi-group mode.
``<cutoff>`` Element
--------------------
@ -212,8 +214,21 @@ cross section values between.
*Default*: logarithm
.. note:: This element is not used in the multi-group :ref:`energy_mode`.
.. _LA-UR-14-24530: https://laws.lanl.gov/vhosts/mcnp.lanl.gov/pdf_files/la-ur-14-24530.pdf
.. _energy_mode:
``<energy_mode>`` Element
-------------------------
The ``<energy_mode>`` element tells OpenMC if the run-mode should be
continuous-energy or multi-group. Options for entry are: ``continuous-energy``
or ``multi-group``.
*Default*: continuous-energy
``<entropy>`` Element
---------------------
@ -264,6 +279,33 @@ based on the recommended value in LA-UR-14-24530_.
*Default*: 8000
.. note:: This element is not used in the multi-group :ref:`energy_mode`.
``<multipole_library>`` Element
-------------------------------
The ``<multipole_library>`` element indicates the directory containing a
windowed multipole library. If a windowed multipole library is available,
OpenMC can use it for on-the-fly Doppler-broadening of resolved resonance range
cross sections. If this element is absent from the settings.xml file, the
:envvar:`OPENMC_MULTIPOLE_LIBRARY` environment variable will be used.
.. note:: The <use_windowed_multipole> element must also be set to "true"
for windowed multipole functionality.
``<max_order>`` Element
---------------------------
The ``<max_order>`` element allows the user to set a maximum scattering order
to apply to every nuclide/material in the problem. That is, if the data
library has :math:`P_3` data available, but ``<max_order>`` was set to ``1``,
then, OpenMC will only use up to the :math:`P_1` data.
*Default*: Use the maximum order in the data library
.. note:: This element is not used in the continuous-energy
:ref:`energy_mode`.
.. _natural_elements:
``<natural_elements>`` Element
@ -312,10 +354,10 @@ out the file and "false" will not.
*Default*: false
:summary:
Writes out an ASCII summary file describing all of the user input files that
Writes out an HDF5 summary file describing all of the user input files that
were read in.
*Default*: false
*Default*: true
:tallies:
Write out an ASCII file of tally results.
@ -343,6 +385,8 @@ or sub-elements and can be set to either "false" or "true".
*Default*: true
.. note:: This element is not used in the multi-group :ref:`energy_mode`.
``<resonance_scattering>`` Element
----------------------------------
@ -402,6 +446,8 @@ attributes or sub-elements:
*Defaults*: None (scatterer), ARES (method), 0.01 eV (E_min), 1.0 keV (E_max)
.. note:: This element is not used in the multi-group :ref:`energy_mode`.
``<run_cmfd>`` Element
----------------------
@ -424,9 +470,17 @@ pseudo-random number generator.
The ``source`` element gives information on an external source distribution to
be used either as the source for a fixed source calculation or the initial
source guess for criticality calculations. It takes the following
source guess for criticality calculations. Multiple ``<source>`` elements may be
specified to define different source distributions. Each one takes the following
attributes/sub-elements:
:strength:
The strength of the source. If multiple sources are present, the source
strength indicates the relative probability of choosing one source over the
other.
*Default*: 1.0
:file:
If this attribute is given, it indicates that the source is to be read from
a binary source file whose path is given by the value of this element. Note,
@ -440,13 +494,13 @@ attributes/sub-elements:
has the following attributes:
:type:
The type of spatial distribution. Valid options are "box", "fission", and
"point". A "box" spatial distribution has coordinates sampled uniformly in
a parallelepiped. A "fission" spatial distribution samples locations from
a "box" distribution but only locations in fissionable materials are
accepted. A "point" spatial distribution has coordinates specified by a
triplet.
The type of spatial distribution. Valid options are "box", "fission",
"point", and "cartesian". A "box" spatial distribution has coordinates
sampled uniformly in a parallelepiped. A "fission" spatial distribution
samples locations from a "box" distribution but only locations in
fissionable materials are accepted. A "point" spatial distribution has
coordinates specified by a triplet. An "cartesian" spatial distribution
specifies independent distributions of x-, y-, and z-coordinates.
*Default*: None
@ -459,67 +513,125 @@ attributes/sub-elements:
For a "point" spatial distribution, ``parameters`` should be given as
three real numbers which specify the (x,y,z) location of an isotropic
point source
point source.
For an "cartesian" distribution, no parameters are specified. Instead,
the ``x``, ``y``, and ``z`` elements must be specified.
*Default*: None
:x:
For an "cartesian" distribution, this element specifies the distribution
of x-coordinates. The necessary sub-elements/attributes are those of a
univariate probability distribution (see the description in
:ref:`univariate`).
:y:
For an "cartesian" distribution, this element specifies the distribution
of y-coordinates. The necessary sub-elements/attributes are those of a
univariate probability distribution (see the description in
:ref:`univariate`).
:z:
For an "cartesian" distribution, this element specifies the distribution
of z-coordinates. The necessary sub-elements/attributes are those of a
univariate probability distribution (see the description in
:ref:`univariate`).
:angle:
An element specifying the angular distribution of source sites. This element
has the following attributes:
:type:
The type of angular distribution. Valid options are "isotropic" and
"monodirectional". The angle of the particle emitted from a source site is
isotropic if the "isotropic" option is given. The angle of the particle
emitted from a source site is the direction specified in the <parameters>
attribute if "monodirectional" option is given.
The type of angular distribution. Valid options are "isotropic",
"monodirectional", and "mu-phi". The angle of the particle emitted from a
source site is isotropic if the "isotropic" option is given. The angle of
the particle emitted from a source site is the direction specified in the
``reference_uvw`` element/attribute if "monodirectional" option is
given. The "mu-phi" option produces directions with the cosine of the
polar angle and the azimuthal angle explicitly specified.
*Default*: isotropic
:parameters:
For an "isotropic" angular distribution, ``parameters`` should not be
specified.
:reference_uvw:
The direction from which the polar angle is measured. Represented by the
x-, y-, and z-components of a unit vector. For a monodirectional
distribution, this defines the direction of all sampled particles.
For a "monodirectional" angular distribution, ``parameters`` should be
given as three real numbers which specify the angular cosines with respect
to each axis.
:mu:
An element specifying the distribution of the cosine of the polar
angle. Only relevant when the type is "mu-phi". The necessary
sub-elements/attributes are those of a univariate probability distribution
(see the description in :ref:`univariate`).
*Default*: None
:phi:
An element specifying the distribution of the azimuthal angle. Only
relevant when the type is "mu-phi". The necessary sub-elements/attributes
are those of a univariate probability distribution (see the description in
:ref:`univariate`).
:energy:
An element specifying the energy distribution of source sites. This element
has the following attributes:
:type:
The type of energy distribution. Valid options are "monoenergetic",
"watt", and "maxwell". The "monoenergetic" option produces source sites at
a single energy. The "watt" option produces source sites whose energy is
sampled from a Watt fission spectrum. The "maxwell" option produce source
sites whose energy is sampled from a Maxwell fission spectrum.
*Default*: watt
:parameters:
For a "monoenergetic" energy distribution, ``parameters`` should be
given as the energy in MeV of the source sites.
For a "watt" energy distribution, ``parameters`` should be given as two
real numbers :math:`a` and :math:`b` that parameterize the distribution
:math:`p(E) dE = c e^{-E/a} \sinh \sqrt{b \, E} dE`.
For a "maxwell" energy distribution, ``parameters`` should be given as one
real number :math:`a` that parameterizes the distribution :math:`p(E) dE =
c E e^{-E/a} dE`.
*Default*: 0.988 2.249
An element specifying the energy distribution of source sites. The necessary
sub-elements/attributes are those of a univariate probability distribution
(see the description in :ref:`univariate`).
:write_initial:
An element specifying whether to write out the initial source bank used at
the beginning of the first batch. The output file is named
"initial_source.binary(h5)"
"initial_source.h5"
*Default*: false
*Default*: false
.. _univariate:
Univariate Probability Distributions
++++++++++++++++++++++++++++++++++++
Various components of a source distribution involve probability distributions of
a single random variable, e.g. the distribution of the energy, the distribution
of the polar angle, and the distribution of x-coordinates. Each of these
components supports the same syntax with an element whose tag signifies the
variable and whose sub-elements/attributes are as follows:
:type:
The type of the distribution. Valid options are "uniform", "discrete",
"tabular", "maxwell", and "watt". The "uniform" option produces variates
sampled from a uniform distribution over a finite interval. The "discrete"
option produces random variates that can assume a finite number of values
(i.e., a distribution characterized by a probability mass function). The
"tabular" option produces random variates sampled from a tabulated
distribution where the density function is either a histogram or
linearly-interpolated between tabulated points. The "watt" option produces
random variates is sampled from a Watt fission spectrum (only used for
energies). The "maxwell" option produce variates sampled from a Maxwell
fission spectrum (only used for energies).
*Default*: None
:parameters:
For a "uniform" distribution, ``parameters`` should be given as two real
numbers :math:`a` and :math:`b` that define the interval :math:`[a,b]` over
which random variates are sampled.
For a "discrete" or "tabular" distribution, ``parameters`` provides the
:math:`(x,p)` pairs defining the discrete/tabular distribution. All :math:`x`
points are given first followed by corresponding :math:`p` points.
For a "watt" distribution, ``parameters`` should be given as two real numbers
:math:`a` and :math:`b` that parameterize the distribution :math:`p(x) dx = c
e^{-x/a} \sinh \sqrt{b \, x} dx`.
For a "maxwell" distribution, ``parameters`` should be given as one real
number :math:`a` that parameterizes the distribution :math:`p(x) dx = c x
e^{-x/a} dx`.
.. note:: The above format should be used even when using the multi-group
:ref:`energy_mode`.
:interpolation:
For a "tabular" distribution, ``interpolation`` can be set to "histogram" or
"linear-linear" thereby specifying how tabular points are to be interpolated.
*Default*: histogram
``<state_point>`` Element
-------------------------
@ -576,7 +688,7 @@ attributes/sub-elements:
*Default*: false
:source_write:
:write:
If this element is set to "false", source sites are not written
to the state point or source point file. This can substantially reduce the
size of state points if large numbers of particles per batch are used.
@ -701,6 +813,17 @@ problem. It has the following attributes/sub-elements:
*Default*: None
``<use_windowed_multipole>`` Element
------------------------------------
The ``<use_windowed_multipole>`` element toggles the windowed multipole
capability on or off. If this element is set to "True" and the relevant data is
available, OpenMC will use the windowed multipole method to evaluate and Doppler
broaden cross sections in the resolved resonance range.
*Default*: False
``<verbosity>`` Element
-----------------------
@ -798,11 +921,19 @@ Each ``<surface>`` element can have the following attributes or sub-elements:
*Default*: None
:boundary:
The boundary condition for the surface. This can be "transmission",
"vacuum", or "reflective".
The boundary condition for the surface. This can be "transmission",
"vacuum", "reflective", or "periodic". Periodic boundary conditions can
only be applied to x-, y-, and z-planes. Only axis-aligned periodicity is
supported, i.e., x-planes can only be paired with x-planes. Specify which
planes are periodic and the code will automatically identify which planes
are paired together.
*Default*: "transmission"
:periodic_surface_id:
If a periodic boundary condition is applied, this attribute identifies the
``id`` of the corresponding periodic sufrace.
The following quadratic surfaces can be modeled:
:x-plane:
@ -891,7 +1022,9 @@ Each ``<cell>`` element can have the following attributes or sub-elements:
:material:
The ``id`` of the material that this cell contains. If the cell should
contain no material, this can also be set to "void".
contain no material, this can also be set to "void". A list of materials
can be specified for the "distributed material" feature. This will give each
unique instance of the cell its own material.
.. note:: If a material is specified, no fill should be given.
@ -921,6 +1054,15 @@ Each ``<cell>`` element can have the following attributes or sub-elements:
*Default*: A region filling all space.
:temperature:
The temperature of the cell in Kelvin. If windowed-multipole data is
avalable, this temperature will be used to Doppler broaden some cross
sections in the resolved resonance region. A list of temperatures can be
specified for the "distributed temperature" feature. This will give each
unique instance of the cell its own temperature.
*Default*: The temperature of the coldest nuclide in the cell's material(s)
:rotation:
If the cell is filled with a universe, this element specifies the angles in
degrees about the x, y, and z axes that the filled universe should be
@ -932,6 +1074,20 @@ Each ``<cell>`` element can have the following attributes or sub-elements:
<cell fill="..." rotation="0 0 90" />
The rotation applied is an intrinsic rotation whose Tait-Bryan angles are
given as those specified about the x, y, and z axes respectively. That is to
say, if the angles are :math:`(\phi, \theta, \psi)`, then the rotation
matrix applied is :math:`R_z(\psi) R_y(\theta) R_x(\phi)` or
.. math::
\left [ \begin{array}{ccc} \cos\theta \cos\psi & -\cos\theta \sin\psi +
\sin\phi \sin\theta \cos\psi & \sin\phi \sin\psi + \cos\phi \sin\theta
\cos\psi \\ \cos\theta \sin\psi & \cos\phi \cos\psi + \sin\phi \sin\theta
\sin\psi & -\sin\phi \cos\psi + \cos\phi \sin\theta \sin\psi \\
-\sin\theta & \sin\phi \cos\theta & \cos\phi \cos\theta \end{array}
\right ]
*Default*: None
:translation:
@ -1114,14 +1270,21 @@ Each ``material`` element can have the following attributes or sub-elements:
An element with attributes/sub-elements called ``value`` and ``units``. The
``value`` attribute is the numeric value of the density while the ``units``
can be "g/cm3", "kg/m3", "atom/b-cm", "atom/cm3", or "sum". The "sum" unit
indicates that values appearing in ``ao`` attributes for ``<nuclide>`` and
``<element>`` sub-elements are to be interpreted as nuclide/element
densities in atom/b-cm, and the total density of the material is taken as
the sum of all nuclides/elements. The "sum" option cannot be used in
conjunction with weight percents.
indicates that values appearing in ``ao`` or ``wo`` attributes for ``<nuclide>``
and ``<element>`` sub-elements are to be interpreted as absolute nuclide/element
densities in atom/b-cm or g/cm3, and the total density of the material is
taken as the sum of all nuclides/elements. The "macro" unit is used with
a ``macroscopic`` quantity to indicate that the density is already included
in the library and thus not needed here. However, if a value is provided
for the ``value``, then this is treated as a number density multiplier on
the macroscopic cross sections in the multi-group data. This can be used,
for example, when perturbing the density slightly.
*Default*: None
.. note:: A ``macroscopic`` quantity can not be used in conjunction with a
``nuclide``, ``element``, or ``sab`` quantity.
:nuclide:
An element with attributes/sub-elements called ``name``, ``xs``, and ``ao``
or ``wo``. The ``name`` attribute is the name of the cross-section for a
@ -1149,6 +1312,9 @@ Each ``material`` element can have the following attributes or sub-elements:
*Default*: None
.. note:: The ``scattering`` attribute/sub-element is not used in the
multi-group :ref:`energy_mode`.
:element:
Specifies that a natural element is present in the material. The natural
@ -1184,6 +1350,9 @@ Each ``material`` element can have the following attributes or sub-elements:
*Default*: None
.. note:: The ``scattering`` attribute/sub-element is not used in the
multi-group :ref:`energy_mode`.
:sab:
Associates an S(a,b) table with the material. This element has
attributes/sub-elements called ``name`` and ``xs``. The ``name`` attribute
@ -1192,6 +1361,26 @@ Each ``material`` element can have the following attributes or sub-elements:
*Default*: None
.. note:: This element is not used in the multi-group :ref:`energy_mode`.
:macroscopic:
The ``macroscopic`` element is similar to the ``nuclide`` element, but,
recognizes that some multi-group libraries may be providing material
specific macroscopic cross sections instead of always providing nuclide
specific data like in the continuous-energy case. To that end, the
macroscopic element has attributes/sub-elements called ``name``, and ``xs``.
The ``name`` attribute is the name of the cross-section for a
desired nuclide while the ``xs`` attribute is the cross-section
identifier. One example would be as follows:
.. code-block:: xml
<macroscopic name="UO2" xs="71c" />
.. note:: This element is only used in the multi-group :ref:`energy_mode`.
*Default*: None
.. _IUPAC Isotopic Compositions of the Elements 2009:
http://pac.iupac.org/publications/pac/pdf/2011/pdf/8302x0397.pdf
@ -1278,7 +1467,8 @@ The ``<tally>`` element accepts the following sub-elements:
A list of universes for which the tally should be accumulated.
:energy:
A monotonically increasing list of bounding **pre-collision** energies
In continuous-energy mode, this filter should be provided as a
monotonically increasing list of bounding **pre-collision** energies
for a number of groups. For example, if this filter is specified as
.. code-block:: xml
@ -1288,17 +1478,24 @@ The ``<tally>`` element accepts the following sub-elements:
then two energy bins will be created, one with energies between 0 and
1 MeV and the other with energies between 1 and 20 MeV.
In multi-group mode the bins provided must match group edges
defined in the multi-group library.
:energyout:
A monotonically increasing list of bounding **post-collision**
energies for a number of groups. For example, if this filter is
specified as
In continuous-energy mode, this filter should be provided as a
monotonically increasing list of bounding **post-collision** energies
for a number of groups. For example, if this filter is specified as
.. code-block:: xml
<filter type="energyout" bins="0.0 1.0 20.0" />
then two post-collision energy bins will be created, one with energies
between 0 and 1 MeV and the other with energies between 1 and 20 MeV.
then two post-collision energy bins will be created, one with
energies between 0 and 1 MeV and the other with energies between
1 and 20 MeV.
In multi-group mode the bins provided must match group edges
defined in the multi-group library.
:mu:
A monotonically increasing list of bounding **post-collision** cosines
@ -1382,6 +1579,8 @@ The ``<tally>`` element accepts the following sub-elements:
<filter type="delayedgroup" bins="1 2 3 4 5 6" />
.. note:: This filter type is not used in the multi-group :ref:`energy_mode`.
:nuclides:
If specified, the scores listed will be for particular nuclides, not the
summation of reactions from all nuclides. The format for nuclides should be
@ -1409,114 +1608,207 @@ The ``<tally>`` element accepts the following sub-elements:
*Default*: ``tracklength`` but will revert to ``analog`` if necessary.
:scores:
A space-separated list of the desired responses to be accumulated. Accepted
options are "flux", "total", "scatter", "absorption", "fission",
"nu-fission", "delayed-nu-fission", "kappa-fission", "nu-scatter",
"scatter-N", "scatter-PN", "scatter-YN", "nu-scatter-N", "nu-scatter-PN",
"nu-scatter-YN", "flux-YN", "total-YN", "current", "inverse-velocity" and
"events". These correspond to the following physical quantities:
A space-separated list of the desired responses to be accumulated. The accepted
options are listed in the following tables:
:flux:
Total flux in particle-cm per source particle.
.. table:: **Flux scores: units are particle-cm per source particle.**
.. note::
The ``analog`` estimator is actually identical to the ``collision``
estimator for the flux score.
+----------------------+---------------------------------------------------+
|Score | Description |
+======================+===================================================+
|flux |Total flux. |
+----------------------+---------------------------------------------------+
|flux-YN |Spherical harmonic expansion of the direction of |
| |motion :math:`\left(\Omega\right)` of the total |
| |flux. This score will tally all of the harmonic |
| |moments of order 0 to N. N must be between 0 and |
| |10. |
+----------------------+---------------------------------------------------+
:total:
Total reaction rate in reactions per source particle.
.. table:: **Reaction scores: units are reactions per source particle.**
:scatter:
Total scattering rate. Can also be identified with the ``scatter-0``
response type. Units are reactions per source particle.
+----------------------+---------------------------------------------------+
|Score | Description |
+======================+===================================================+
|absorption |Total absorption rate. This accounts for all |
| |reactions which do not produce secondary neutrons |
| |as well as fission. |
+----------------------+---------------------------------------------------+
|elastic |Elastic scattering reaction rate. |
+----------------------+---------------------------------------------------+
|fission |Total fission reaction rate. |
+----------------------+---------------------------------------------------+
|scatter |Total scattering rate. Can also be identified with |
| |the "scatter-0" response type. |
+----------------------+---------------------------------------------------+
|scatter-N |Tally the N\ :sup:`th` \ scattering moment, where N|
| |is the Legendre expansion order of the change in |
| |particle angle :math:`\left(\mu\right)`. N must be |
| |between 0 and 10. As an example, tallying the 2\ |
| |:sup:`nd` \ scattering moment would be specified as|
| |``<scores>scatter-2</scores>``. |
+----------------------+---------------------------------------------------+
|scatter-PN |Tally all of the scattering moments from order 0 to|
| |N, where N is the Legendre expansion order of the |
| |change in particle angle |
| |:math:`\left(\mu\right)`. That is, "scatter-P1" is |
| |equivalent to requesting tallies of "scatter-0" and|
| |"scatter-1". Like for "scatter-N", N must be |
| |between 0 and 10. As an example, tallying up to the|
| |2\ :sup:`nd` \ scattering moment would be specified|
| |as ``<scores> scatter-P2 </scores>``. |
+----------------------+---------------------------------------------------+
|scatter-YN |"scatter-YN" is similar to "scatter-PN" except an |
| |additional expansion is performed for the incoming |
| |particle direction :math:`\left(\Omega\right)` |
| |using the real spherical harmonics. This is useful|
| |for performing angular flux moment weighting of the|
| |scattering moments. Like "scatter-PN", "scatter-YN"|
| |will tally all of the moments from order 0 to N; N |
| |again must be between 0 and 10. |
+----------------------+---------------------------------------------------+
|total |Total reaction rate. |
+----------------------+---------------------------------------------------+
|total-YN |The total reaction rate expanded via spherical |
| |harmonics about the direction of motion of the |
| |neutron, :math:`\Omega`. This score will tally all |
| |of the harmonic moments of order 0 to N. N must be|
| |between 0 and 10. |
+----------------------+---------------------------------------------------+
|(n,2nd) |(n,2nd) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,2n) |(n,2n) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,3n) |(n,3n) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,na) |(n,n\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,n3a) |(n,n3\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,2na) |(n,2n\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,3na) |(n,3n\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,np) |(n,np) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,n2a) |(n,n2\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,2n2a) |(n,2n2\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,nd) |(n,nd) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,nt) |(n,nt) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,nHe-3) |(n,n\ :sup:`3`\ He) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,nd2a) |(n,nd2\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,nt2a) |(n,nt2\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,4n) |(n,4n) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,2np) |(n,2np) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,3np) |(n,3np) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,n2p) |(n,n2p) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,n*X*) |Level inelastic scattering reaction rate. The *X* |
| |indicates what which inelastic level, e.g., (n,n3) |
| |is third-level inelastic scattering. |
+----------------------+---------------------------------------------------+
|(n,nc) |Continuum level inelastic scattering reaction rate.|
+----------------------+---------------------------------------------------+
|(n,gamma) |Radiative capture reaction rate. |
+----------------------+---------------------------------------------------+
|(n,p) |(n,p) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,d) |(n,d) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,t) |(n,t) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,3He) |(n,\ :sup:`3`\ He) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,a) |(n,\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,2a) |(n,2\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,3a) |(n,3\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,2p) |(n,2p) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,pa) |(n,p\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,t2a) |(n,t2\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,d2a) |(n,d2\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,pd) |(n,pd) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,pt) |(n,pt) reaction rate. |
+----------------------+---------------------------------------------------+
|(n,da) |(n,d\ :math:`\alpha`\ ) reaction rate. |
+----------------------+---------------------------------------------------+
|*Arbitrary integer* |An arbitrary integer is interpreted to mean the |
| |reaction rate for a reaction with a given ENDF MT |
| |number. |
+----------------------+---------------------------------------------------+
:absorption:
Total absorption rate. This accounts for all reactions which do not
produce secondary neutrons. Units are reactions per source particle.
.. table:: **Particle production scores: units are particles produced per
source particles.**
:fission:
Total fission rate in reactions per source particle.
+----------------------+---------------------------------------------------+
|Score | Description |
+======================+===================================================+
|delayed-nu-fission |Total production of delayed neutrons due to |
| |fission. This score type is not used in the |
| |multi-group :ref:`energy_mode`. |
+----------------------+---------------------------------------------------+
|nu-fission |Total production of neutrons due to fission. |
+----------------------+---------------------------------------------------+
|nu-scatter, |These scores are similar in functionality to their |
|nu-scatter-N, |``scatter*`` equivalents except the total |
|nu-scatter-PN, |production of neutrons due to scattering is scored |
|nu-scatter-YN |vice simply the scattering rate. This accounts for |
| |multiplicity from (n,2n), (n,3n), and (n,4n) |
| |reactions. |
+----------------------+---------------------------------------------------+
:nu-fission:
Total production of neutrons due to fission. Units are neutrons produced
per source neutron.
.. table:: **Miscellaneous scores: units are indicated for each.**
:delayed-nu-fission:
Total production of delayed neutrons due to fission. Units are neutrons produced
per source neutron.
+----------------------+---------------------------------------------------+
|Score | Description |
+======================+===================================================+
|current |Partial currents on the boundaries of each cell in |
| |a mesh. Units are particles per source |
| |particle. Note that this score can only be used if |
| |a mesh filter has been specified. Furthermore, it |
| |may not be used in conjunction with any other |
| |score. |
+----------------------+---------------------------------------------------+
|events |Number of scoring events. Units are events per |
| |source particle. |
+----------------------+---------------------------------------------------+
|inverse-velocity |The flux-weighted inverse velocity where the |
| |velocity is in units of centimeters per second. |
| |This score type is not used in the |
| |multi-group :ref:`energy_mode`. |
+----------------------+---------------------------------------------------+
|kappa-fission |The recoverable energy production rate due to |
| |fission. The recoverable energy is defined as the |
| |fission product kinetic energy, prompt and delayed |
| |neutron kinetic energies, prompt and delayed |
| |:math:`\gamma`-ray total energies, and the total |
| |energy released by the delayed :math:`\beta` |
| |particles. The neutrino energy does not contribute |
| |to this response. The prompt and delayed |
| |:math:`\gamma`-rays are assumed to deposit their |
| |energy locally. Units are MeV per source particle. |
+----------------------+---------------------------------------------------+
:kappa-fission:
The recoverable energy production rate due to fission. The recoverable
energy is defined as the fission product kinetic energy, prompt and
delayed neutron kinetic energies, prompt and delayed :math:`\gamma`-ray
total energies, and the total energy released by the delayed :math:`\beta`
particles. The neutrino energy does not contribute to this response. The
prompt and delayed :math:`\gamma`-rays are assumed to deposit their energy
locally. Units are MeV per source particle.
:scatter-N:
Tally the N\ :sup:`th` \ scattering moment, where N is the Legendre
expansion order of the change in particle angle :math:`\left(\mu\right)`.
N must be between 0 and 10. As an example, tallying the 2\ :sup:`nd` \
scattering moment would be specified as ``<scores> scatter-2
</scores>``. Units are reactions per source particle.
:scatter-PN:
Tally all of the scattering moments from order 0 to N, where N is the
Legendre expansion order of the change in particle angle
:math:`\left(\mu\right)`. That is, ``scatter-P1`` is equivalent to
requesting tallies of ``scatter-0`` and ``scatter-1``. Like for
``scatter-N``, N must be between 0 and 10. As an example, tallying up to
the 2\ :sup:`nd` \ scattering moment would be specified as ``<scores>
scatter-P2 </scores>``. Units are reactions per source particle.
:scatter-YN:
``scatter-YN`` is similar to ``scatter-PN`` except an additional expansion
is performed for the incoming particle direction
:math:`\left(\Omega\right)` using the real spherical harmonics. This is
useful for performing angular flux moment weighting of the scattering
moments. Like ``scatter-PN``, ``scatter-YN`` will tally all of the moments
from order 0 to N; N again must be between 0 and 10. Units are reactions
per source particle.
:nu-scatter, nu-scatter-N, nu-scatter-PN, nu-scatter-YN:
These scores are similar in functionality to their ``scatter*``
equivalents except the total production of neutrons due to scattering is
scored vice simply the scattering rate. This accounts for multiplicity
from (n,2n), (n,3n), and (n,4n) reactions. Units are neutrons produced per
source particle.
:flux-YN:
Spherical harmonic expansion of the direction of motion
:math:`\left(\Omega\right)` of the total flux. This score will tally all
of the harmonic moments of order 0 to N. N must be between 0
and 10. Units are particle-cm per source particle.
:total-YN:
The total reaction rate expanded via spherical harmonics about the
direction of motion of the neutron, :math:`\Omega`.
This score will tally all of the harmonic moments of order 0 to N. N must
be between 0 and 10. Units are reactions per source particle.
:current:
Partial currents on the boundaries of each cell in a mesh. Units are
particles per source particle.
.. note::
This score can only be used if a mesh filter has been
specified. Furthermore, it may not be used in conjunction with any
other score.
:inverse-velocity:
The flux-weighted inverse velocity where the velocity is in units of
centimeters per second.
.. note::
The ``analog`` estimator is actually identical to the ``collision``
estimator for the inverse-velocity score.
:events:
Number of scoring events. Units are events per source particle.
.. note::
The ``analog`` estimator is actually identical to the ``collision``
estimator for the flux and inverse-velocity scores.
:trigger:
Precision trigger applied to all filter bins and nuclides for this tally.
@ -1671,7 +1963,7 @@ sub-elements:
datafiles can be processed into 3D SILO files using the
``openmc-voxel-to-silovtk`` utility provided with the OpenMC source, and
subsequently viewed with a 3D viewer such as VISIT or Paraview. See the
:ref:`usersguide_voxel` for information about the datafile structure.
:ref:`io_voxel` for information about the datafile structure.
.. note:: Since the PPM format is saved without any kind of compression,
the resulting file sizes can be quite large. Saving the image in

59
docs/source/usersguide/install.rst
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@ -9,8 +9,8 @@ Installing on Ubuntu with PPA
-----------------------------
For users with Ubuntu 15.04 or later, a binary package for OpenMC is available
through a Personal Package Archive (PPA) and can be installed through the APT
package manager. First, add the following PPA to the repository sources:
through a `Personal Package Archive`_ (PPA) and can be installed through the
`APT package manager`_. First, add the following PPA to the repository sources:
.. code-block:: sh
@ -31,10 +31,15 @@ Now OpenMC should be recognized within the repository and can be installed:
Binary packages from this PPA may exist for earlier versions of Ubuntu, but they
are no longer supported.
.. _Personal Package Archive: https://launchpad.net/~paulromano/+archive/staging
.. _APT package manager: https://help.ubuntu.com/community/AptGet/Howto
--------------------
Building from Source
--------------------
.. _prerequisites:
Prerequisites
-------------
@ -222,6 +227,7 @@ your PATH environment variable and subsequently uses it to determine library
locations and compile flags. If you have multiple installations of HDF5 or one
that does not appear on your PATH, you can set the HDF5_ROOT environment
variable to the root directory of the HDF5 installation, e.g.
.. code-block:: sh
export HDF5_ROOT=/opt/hdf5/1.8.15
@ -350,7 +356,7 @@ Testing Build
-------------
If you have ENDF/B-VII.1 cross sections from NNDC_ you can test your build.
Make sure the **CROSS_SECTIONS** environmental variable is set to the
Make sure the **OPENMC_CROSS_SECTIONS** environmental variable is set to the
*cross_sections.xml* file in the *data/nndc* directory.
There are two ways to run tests. The first is to use the Makefile present in
the source directory and run the following:
@ -375,11 +381,17 @@ Cross Section Configuration
---------------------------
In order to run a simulation with OpenMC, you will need cross section data for
each nuclide in your problem. Since OpenMC uses ACE format cross sections, you
can use nuclear data that was processed with NJOY_, such as that distributed
with MCNP_ or Serpent_. Several sources provide free processed ACE data as
described below. The TALYS-based evaluated nuclear data library, TENDL_, is also
openly available in ACE format.
each nuclide or material in your problem. OpenMC can be run in
continuous-energy or multi-group mode.
In continuous-energy mode OpenMC uses ACE format cross sections; in this case
you can use nuclear data that was processed with NJOY_, such as that
distributed with MCNP_ or Serpent_. Several sources provide free processed
ACE data as described below. The TALYS-based evaluated nuclear data library,
TENDL_, is also openly available in ACE format.
In multi-group mode, OpenMC utilizes an XML-based library format which can be
used to describe nuclide- or material-specific quantities.
Using ENDF/B-VII.1 Cross Sections from NNDC
-------------------------------------------
@ -394,9 +406,10 @@ extract, and set up a confiuration file:
cd openmc/data
python get_nndc_data.py
At this point, you should set the :envvar:`CROSS_SECTIONS` environment variable
to the absolute path of the file ``openmc/data/nndc/cross_sections.xml``. This
cross section set is used by the test suite.
At this point, you should set the :envvar:`OPENMC_CROSS_SECTIONS` environment
variable to the absolute path of the file
``openmc/data/nndc/cross_sections.xml``. This cross section set is used by the
test suite.
Using JEFF Cross Sections from OECD/NEA
---------------------------------------
@ -422,8 +435,8 @@ the following steps must be taken:
4. Additionally, you may need to change any occurrences of upper-case "ACE"
within the ``cross_sections.xml`` file to lower-case.
5. Either set the :ref:`cross_sections` in a settings.xml file or the
:envvar:`CROSS_SECTIONS` environment variable to the absolute path of the
``cross_sections.xml`` file.
:envvar:`OPENMC_CROSS_SECTIONS` environment variable to the absolute path of
the ``cross_sections.xml`` file.
Using Cross Sections from MCNP
------------------------------
@ -431,8 +444,9 @@ Using Cross Sections from MCNP
To use cross sections distributed with MCNP, change the <directory> element in
the ``cross_sections.xml`` file in the root directory of the OpenMC distribution
to the location of the MCNP cross sections. Then, either set the
:ref:`cross_sections` in a settings.xml file or the :envvar:`CROSS_SECTIONS`
environment variable to the absolute path of the ``cross_sections.xml`` file.
:ref:`cross_sections` in a settings.xml file or the
:envvar:`OPENMC_CROSS_SECTIONS` environment variable to the absolute path of
the ``cross_sections.xml`` file.
Using Cross Sections from Serpent
---------------------------------
@ -440,10 +454,21 @@ Using Cross Sections from Serpent
To use cross sections distributed with Serpent, change the <directory> element
in the ``cross_sections_serpent.xml`` file in the root directory of the OpenMC
distribution to the location of the Serpent cross sections. Then, either set the
:ref:`cross_sections` in a settings.xml file or the :envvar:`CROSS_SECTIONS`
environment variable to the absolute path of the ``cross_sections_serpent.xml``
:ref:`cross_sections` in a settings.xml file or the
:envvar:`OPENMC_CROSS_SECTIONS` environment variable to the absolute path of
the ``cross_sections_serpent.xml``
file.
Using Multi-Group Cross Sections
--------------------------------
Multi-group cross section libraries are generally tailored to the specific
calculation to be performed. Therefore, at this point in time, OpenMC is not
distributed with any pre-existing multi-group cross section libraries.
However, if the user has obtained or generated their own library, the user
should set the :envvar:`OPENMC_MG_CROSS_SECTIONS` environment variable
to the absolute path of the file library expected to used most frequently.
.. _NJOY: http://t2.lanl.gov/nis/codes.shtml
.. _NNDC: http://www.nndc.bnl.gov/endf/b7.1/acefiles.html
.. _NEA: http://www.oecd-nea.org

16
docs/source/usersguide/output/index.rst
View file

@ -1,16 +0,0 @@
.. _usersguide_output:
===================
Output File Formats
===================
.. toctree::
:numbered:
:maxdepth: 3
statepoint
source
summary
particle_restart
track
voxel

12
docs/source/usersguide/processing.rst
View file

@ -161,7 +161,7 @@ or
* `VTK <http://www.vtk.org/>`_ with python bindings. On debian derivatives,
these are easily obtained with ``sudo apt-get install python-vtk``
For the HDF5 file structure, see :ref:`usersguide_voxel`.
For the HDF5 file structure, see :ref:`io_voxel`.
Once processed into a standard 3D file format, colors and masks can be defined
using the stored id numbers to better explore the geometry. The process for
@ -195,11 +195,11 @@ Data Extraction
---------------
A great deal of information is available in statepoint files (See
:ref:`usersguide_statepoint`), all of which is accessible through the Python
API. The ``openmc.statepoint`` module (see :ref:`pythonapi_statepoint`) provides
a class to load statepoints and access data as requested; it is used in many of
the provided plotting utilities, OpenMC's regression test suite, and can be used
in user-created scripts to carry out manipulations of the data.
:ref:`io_statepoint`), all of which is accessible through the Python
API. The :class:`openmc.StatePoint` class can load statepoints and access data
as requested; it is used in many of the provided plotting utilities, OpenMC's
regression test suite, and can be used in user-created scripts to carry out
manipulations of the data.
An :ref:`example IPython notebook <notebook_post_processing>` demonstrates how
to extract data from a statepoint using the Python API.

5
docs/sphinxext/notebook_sphinxext.py
View file

@ -12,10 +12,7 @@ from docutils.parsers.rst import directives, roles, states
from docutils.parsers.rst.roles import set_classes
from docutils.transforms import misc
try:
from IPython.nbconver.exporters import html
except ImportError:
from IPython.nbconvert import html
from nbconvert import html
class Notebook(Directive):

66
examples/python/basic/build-xml.py
View file

@ -1,5 +1,6 @@
import openmc
###############################################################################
# Simulation Input File Parameters
###############################################################################
@ -11,7 +12,7 @@ particles = 10000
###############################################################################
# Exporting to OpenMC materials.xml File
# Exporting to OpenMC materials.xml file
###############################################################################
# Instantiate some Nuclides
@ -30,15 +31,14 @@ fuel = openmc.Material(material_id=40, name='fuel')
fuel.set_density('g/cc', 4.5)
fuel.add_nuclide(u235, 1.)
# Instantiate a MaterialsFile, register all Materials, and export to XML
materials_file = openmc.MaterialsFile()
# Instantiate a Materials collection and export to XML
materials_file = openmc.Materials([moderator, fuel])
materials_file.default_xs = '71c'
materials_file.add_materials([moderator, fuel])
materials_file.export_to_xml()
###############################################################################
# Exporting to OpenMC geometry.xml File
# Exporting to OpenMC geometry.xml file
###############################################################################
# Instantiate ZCylinder surfaces
@ -73,31 +73,31 @@ cell1.fill = universe1
universe1.add_cells([cell2, cell3])
root.add_cells([cell1, cell4])
# Instantiate a Geometry and register the root Universe
geometry = openmc.Geometry()
geometry.root_universe = root
# Instantiate a GeometryFile, register Geometry, and export to XML
geometry_file = openmc.GeometryFile()
geometry_file.geometry = geometry
geometry_file.export_to_xml()
# Instantiate a Geometry, register the root Universe, and export to XML
geometry = openmc.Geometry(root)
geometry.export_to_xml()
###############################################################################
# Exporting to OpenMC settings.xml File
# Exporting to OpenMC settings.xml file
###############################################################################
# Instantiate a SettingsFile, set all runtime parameters, and export to XML
settings_file = openmc.SettingsFile()
# Instantiate a Settings object, set all runtime parameters, and export to XML
settings_file = openmc.Settings()
settings_file.batches = batches
settings_file.inactive = inactive
settings_file.particles = particles
settings_file.set_source_space('box', [-4, -4, -4, 4, 4, 4])
# Create an initial uniform spatial source distribution over fissionable zones
bounds = [-4., -4., -4., 4., 4., 4.]
uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:], only_fissionable=True)
settings_file.source = openmc.source.Source(space=uniform_dist)
settings_file.export_to_xml()
###############################################################################
# Exporting to OpenMC tallies.xml File
# Exporting to OpenMC tallies.xml file
###############################################################################
# Instantiate some tally Filters
@ -107,33 +107,21 @@ energyout_filter = openmc.Filter(type='energyout', bins=[0., 20.])
# Instantiate the first Tally
first_tally = openmc.Tally(tally_id=1, name='first tally')
first_tally.add_filter(cell_filter)
scores = ['total', 'scatter', 'nu-scatter', \
first_tally.filters = [cell_filter]
scores = ['total', 'scatter', 'nu-scatter',
'absorption', 'fission', 'nu-fission']
for score in scores:
first_tally.add_score(score)
first_tally.scores = scores
# Instantiate the second Tally
second_tally = openmc.Tally(tally_id=2, name='second tally')
second_tally.add_filter(cell_filter)
second_tally.add_filter(energy_filter)
scores = ['total', 'scatter', 'nu-scatter', \
'absorption', 'fission', 'nu-fission']
for score in scores:
second_tally.add_score(score)
second_tally.filters = [cell_filter, energy_filter]
second_tally.scores = scores
# Instantiate the third Tally
third_tally = openmc.Tally(tally_id=3, name='third tally')
third_tally.add_filter(cell_filter)
third_tally.add_filter(energy_filter)
third_tally.add_filter(energyout_filter)
scores = ['scatter', 'nu-scatter', 'nu-fission']
for score in scores:
third_tally.add_score(score)
third_tally.filters = [cell_filter, energy_filter, energyout_filter]
third_tally.scores = ['scatter', 'nu-scatter', 'nu-fission']
# Instantiate a TalliesFile, register all Tallies, and export to XML
tallies_file = openmc.TalliesFile()
tallies_file.add_tally(first_tally)
tallies_file.add_tally(second_tally)
tallies_file.add_tally(third_tally)
# Instantiate a Tallies collection and export to XML
tallies_file = openmc.Tallies((first_tally, second_tally, third_tally))
tallies_file.export_to_xml()

34
examples/python/boxes/build-xml.py
View file

@ -1,5 +1,4 @@
import numpy as np
import openmc
###############################################################################
@ -37,15 +36,14 @@ moderator.add_nuclide(h1, 2.)
moderator.add_nuclide(o16, 1.)
moderator.add_s_alpha_beta('HH2O', '71t')
# Instantiate a MaterialsFile, register all Materials, and export to XML
materials_file = openmc.MaterialsFile()
# Instantiate a Materials collection and export to XML
materials_file = openmc.Materials([fuel1, fuel2, moderator])
materials_file.default_xs = '71c'
materials_file.add_materials([fuel1, fuel2, moderator])
materials_file.export_to_xml()
###############################################################################
# Exporting to OpenMC geometry.xml File
# Exporting to OpenMC geometry.xml file
###############################################################################
# Instantiate planar surfaces
@ -98,26 +96,25 @@ outer_box.fill = moderator
root = openmc.Universe(universe_id=0, name='root universe')
root.add_cells([inner_box, middle_box, outer_box])
# Instantiate a Geometry and register the root Universe
geometry = openmc.Geometry()
geometry.root_universe = root
# Instantiate a GeometryFile, register Geometry, and export to XML
geometry_file = openmc.GeometryFile()
geometry_file.geometry = geometry
geometry_file.export_to_xml()
# Instantiate a Geometry, register the root Universe, and export to XML
geometry = openmc.Geometry(root)
geometry.export_to_xml()
###############################################################################
# Exporting to OpenMC settings.xml File
###############################################################################
# Instantiate a SettingsFile, set all runtime parameters, and export to XML
settings_file = openmc.SettingsFile()
# Instantiate a Settings object, set all runtime parameters, and export to XML
settings_file = openmc.Settings()
settings_file.batches = batches
settings_file.inactive = inactive
settings_file.particles = particles
settings_file.set_source_space('box', np.concatenate(outer_cube.bounding_box))
# Create an initial uniform spatial source distribution over fissionable zones
uniform_dist = openmc.stats.Box(*outer_cube.bounding_box, only_fissionable=True)
settings_file.source = openmc.source.Source(space=uniform_dist)
settings_file.export_to_xml()
###############################################################################
@ -130,7 +127,6 @@ plot.width = [20, 20]
plot.pixels = [200, 200]
plot.color = 'cell'
# Instantiate a PlotsFile, add Plot, and export to XML
plot_file = openmc.PlotsFile()
plot_file.add_plot(plot)
# Instantiate a Plots collection and export to XML
plot_file = openmc.Plots([plot])
plot_file.export_to_xml()

49
examples/python/lattice/hexagonal/build-xml.py
View file

@ -1,6 +1,5 @@
import openmc
###############################################################################
# Simulation Input File Parameters
###############################################################################
@ -36,15 +35,14 @@ iron = openmc.Material(material_id=3, name='iron')
iron.set_density('g/cc', 7.9)
iron.add_nuclide(fe56, 1.)
# Instantiate a MaterialsFile, register all Materials, and export to XML
materials_file = openmc.MaterialsFile()
# Instantiate a Materials collection and export to XML
materials_file = openmc.Materials([moderator, fuel, iron])
materials_file.default_xs = '71c'
materials_file.add_materials([moderator, fuel, iron])
materials_file.export_to_xml()
###############################################################################
# Exporting to OpenMC geometry.xml File
# Exporting to OpenMC geometry.xml file
###############################################################################
# Instantiate Surfaces
@ -106,26 +104,26 @@ lattice.outer = univ2
# Fill Cell with the Lattice
cell1.fill = lattice
# Instantiate a Geometry and register the root Universe
geometry = openmc.Geometry()
geometry.root_universe = root
# Instantiate a GeometryFile, register Geometry, and export to XML
geometry_file = openmc.GeometryFile()
geometry_file.geometry = geometry
geometry_file.export_to_xml()
# Instantiate a Geometry, register the root Universe, and export to XML
geometry = openmc.Geometry(root)
geometry.export_to_xml()
###############################################################################
# Exporting to OpenMC settings.xml File
# Exporting to OpenMC settings.xml file
###############################################################################
# Instantiate a SettingsFile, set all runtime parameters, and export to XML
settings_file = openmc.SettingsFile()
# Instantiate a Settings object, set all runtime parameters, and export to XML
settings_file = openmc.Settings()
settings_file.batches = batches
settings_file.inactive = inactive
settings_file.particles = particles
settings_file.set_source_space('box', [-1, -1, -1, 1, 1, 1])
# Create an initial uniform spatial source distribution over fissionable zones
bounds = [-1, -1, -1, 1, 1, 1]
uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:], only_fissionable=True)
settings_file.source = openmc.source.Source(space=uniform_dist)
settings_file.keff_trigger = {'type' : 'std_dev', 'threshold' : 5E-4}
settings_file.trigger_active = True
settings_file.trigger_max_batches = 100
@ -133,7 +131,7 @@ settings_file.export_to_xml()
###############################################################################
# Exporting to OpenMC plots.xml File
# Exporting to OpenMC plots.xml file
###############################################################################
plot_xy = openmc.Plot(plot_id=1)
@ -151,10 +149,8 @@ plot_yz.width = [8, 8]
plot_yz.pixels = [400, 400]
plot_yz.color = 'mat'
# Instantiate a PlotsFile, add Plot, and export to XML
plot_file = openmc.PlotsFile()
plot_file.add_plot(plot_xy)
plot_file.add_plot(plot_yz)
# Instantiate a Plots collection, add plots, and export to XML
plot_file = openmc.Plots((plot_xy, plot_yz))
plot_file.export_to_xml()
@ -164,10 +160,9 @@ plot_file.export_to_xml()
# Instantiate a distribcell Tally
tally = openmc.Tally(tally_id=1)
tally.add_filter(openmc.Filter(type='distribcell', bins=[cell2.id]))
tally.add_score('total')
tally.filters = [openmc.Filter(type='distribcell', bins=[cell2.id])]
tally.scores = ['total']
# Instantiate a TalliesFile, register Tally/Mesh, and export to XML
tallies_file = openmc.TalliesFile()
tallies_file.add_tally(tally)
# Instantiate a Tallies collection and export to XML
tallies_file = openmc.Tallies([tally])
tallies_file.export_to_xml()

55
examples/python/lattice/nested/build-xml.py
View file

@ -1,6 +1,5 @@
import openmc
###############################################################################
# Simulation Input File Parameters
###############################################################################
@ -12,7 +11,7 @@ particles = 10000
###############################################################################
# Exporting to OpenMC materials.xml File
# Exporting to OpenMC materials.xml file
###############################################################################
# Instantiate some Nuclides
@ -31,15 +30,14 @@ moderator.add_nuclide(h1, 2.)
moderator.add_nuclide(o16, 1.)
moderator.add_s_alpha_beta('HH2O', '71t')
# Instantiate a MaterialsFile, register all Materials, and export to XML
materials_file = openmc.MaterialsFile()
# Instantiate a Materials collection and export to XML
materials_file = openmc.Materials((moderator, fuel))
materials_file.default_xs = '71c'
materials_file.add_materials([moderator, fuel])
materials_file.export_to_xml()
###############################################################################
# Exporting to OpenMC geometry.xml File
# Exporting to OpenMC geometry.xml file
###############################################################################
# Instantiate Surfaces
@ -100,14 +98,12 @@ univ4.add_cell(cell2)
# Instantiate nested Lattices
lattice1 = openmc.RectLattice(lattice_id=4, name='4x4 assembly')
lattice1.dimension = [2, 2]
lattice1.lower_left = [-1., -1.]
lattice1.pitch = [1., 1.]
lattice1.universes = [[univ1, univ2],
[univ2, univ3]]
lattice2 = openmc.RectLattice(lattice_id=6, name='4x4 core')
lattice2.dimension = [2, 2]
lattice2.lower_left = [-2., -2.]
lattice2.pitch = [2., 2.]
lattice2.universes = [[univ4, univ4],
@ -117,31 +113,31 @@ lattice2.universes = [[univ4, univ4],
cell1.fill = lattice2
cell2.fill = lattice1
# Instantiate a Geometry and register the root Universe
geometry = openmc.Geometry()
geometry.root_universe = root
# Instantiate a GeometryFile, register Geometry, and export to XML
geometry_file = openmc.GeometryFile()
geometry_file.geometry = geometry
geometry_file.export_to_xml()
# Instantiate a Geometry, register the root Universe, and export to XML
geometry = openmc.Geometry(root)
geometry.export_to_xml()
###############################################################################
# Exporting to OpenMC settings.xml File
# Exporting to OpenMC settings.xml file
###############################################################################
# Instantiate a SettingsFile, set all runtime parameters, and export to XML
settings_file = openmc.SettingsFile()
# Instantiate a Settings object, set all runtime parameters, and export to XML
settings_file = openmc.Settings()
settings_file.batches = batches
settings_file.inactive = inactive
settings_file.particles = particles
settings_file.set_source_space('box', [-1, -1, -1, 1, 1, 1])
# Create an initial uniform spatial source distribution over fissionable zones
bounds = [-1, -1, -1, 1, 1, 1]
uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:], only_fissionable=True)
settings_file.source = openmc.source.Source(space=uniform_dist)
settings_file.export_to_xml()
###############################################################################
# Exporting to OpenMC plots.xml File
# Exporting to OpenMC plots.xml file
###############################################################################
plot = openmc.Plot(plot_id=1)
@ -150,14 +146,13 @@ plot.width = [4, 4]
plot.pixels = [400, 400]
plot.color = 'mat'
# Instantiate a PlotsFile, add Plot, and export to XML
plot_file = openmc.PlotsFile()
plot_file.add_plot(plot)
# Instantiate a Plots object and export to XML
plot_file = openmc.Plots([plot])
plot_file.export_to_xml()
###############################################################################
# Exporting to OpenMC tallies.xml File
# Exporting to OpenMC tallies.xml file
###############################################################################
# Instantiate a tally mesh
@ -173,11 +168,9 @@ mesh_filter.mesh = mesh
# Instantiate the Tally
tally = openmc.Tally(tally_id=1)
tally.add_filter(mesh_filter)
tally.add_score('total')
tally.filters = [mesh_filter]
tally.scores = ['total']
# Instantiate a TalliesFile, register Tally/Mesh, and export to XML
tallies_file = openmc.TalliesFile()
tallies_file.add_mesh(mesh)
tallies_file.add_tally(tally)
# Instantiate a Tallies collection, register Tally/Mesh, and export to XML
tallies_file = openmc.Tallies([tally])
tallies_file.export_to_xml()

57
examples/python/lattice/simple/build-xml.py
View file

@ -11,7 +11,7 @@ particles = 10000
###############################################################################
# Exporting to OpenMC materials.xml File
# Exporting to OpenMC materials.xml file
###############################################################################
# Instantiate some Nuclides
@ -30,15 +30,14 @@ moderator.add_nuclide(h1, 2.)
moderator.add_nuclide(o16, 1.)
moderator.add_s_alpha_beta('HH2O', '71t')
# Instantiate a MaterialsFile, register all Materials, and export to XML
materials_file = openmc.MaterialsFile()
# Instantiate a Materials collection and export to XML
materials_file = openmc.Materials([moderator, fuel])
materials_file.default_xs = '71c'
materials_file.add_materials([moderator, fuel])
materials_file.export_to_xml()
###############################################################################
# Exporting to OpenMC geometry.xml File
# Exporting to OpenMC geometry.xml file
###############################################################################
# Instantiate Surfaces
@ -95,7 +94,6 @@ root.add_cell(cell1)
# Instantiate a Lattice
lattice = openmc.RectLattice(lattice_id=5)
lattice.dimension = [4, 4]
lattice.lower_left = [-2., -2.]
lattice.pitch = [1., 1.]
lattice.universes = [[univ1, univ2, univ1, univ2],
@ -106,33 +104,33 @@ lattice.universes = [[univ1, univ2, univ1, univ2],
# Fill Cell with the Lattice
cell1.fill = lattice
# Instantiate a Geometry and register the root Universe
geometry = openmc.Geometry()
geometry.root_universe = root
# Instantiate a GeometryFile, register Geometry, and export to XML
geometry_file = openmc.GeometryFile()
geometry_file.geometry = geometry
geometry_file.export_to_xml()
# Instantiate a Geometry, register the root Universe, and export to XML
geometry = openmc.Geometry(root)
geometry.export_to_xml()
###############################################################################
# Exporting to OpenMC settings.xml File
# Exporting to OpenMC settings.xml file
###############################################################################
# Instantiate a SettingsFile, set all runtime parameters, and export to XML
settings_file = openmc.SettingsFile()
# Instantiate a Settings object, set all runtime parameters, and export to XML
settings_file = openmc.Settings()
settings_file.batches = batches
settings_file.inactive = inactive
settings_file.particles = particles
settings_file.set_source_space('box', [-1, -1, -1, 1, 1, 1])
# Create an initial uniform spatial source distribution over fissionable zones
bounds = [-1, -1, -1, 1, 1, 1]
uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:], only_fissionable=True)
settings_file.source = openmc.source.Source(space=uniform_dist)
settings_file.trigger_active = True
settings_file.trigger_max_batches = 100
settings_file.export_to_xml()
###############################################################################
# Exporting to OpenMC plots.xml File
# Exporting to OpenMC plots.xml file
###############################################################################
plot = openmc.Plot(plot_id=1)
@ -141,14 +139,13 @@ plot.width = [4, 4]
plot.pixels = [400, 400]
plot.color = 'mat'
# Instantiate a PlotsFile, add Plot, and export to XML
plot_file = openmc.PlotsFile()
plot_file.add_plot(plot)
# Instantiate a Plots collection and export to XML
plot_file = openmc.Plots([plot])
plot_file.export_to_xml()
###############################################################################
# Exporting to OpenMC tallies.xml File
# Exporting to OpenMC tallies.xml file
###############################################################################
# Instantiate a tally mesh
@ -164,16 +161,14 @@ mesh_filter.mesh = mesh
# Instantiate tally Trigger
trigger = openmc.Trigger(trigger_type='rel_err', threshold=1E-2)
trigger.add_score('all')
trigger.scores = ['all']
# Instantiate the Tally
tally = openmc.Tally(tally_id=1)
tally.add_filter(mesh_filter)
tally.add_score('total')
tally.add_trigger(trigger)
tally.filters = [mesh_filter]
tally.scores = ['total']
tally.triggers = [trigger]
# Instantiate a TalliesFile, register Tally/Mesh, and export to XML
tallies_file = openmc.TalliesFile()
tallies_file.add_mesh(mesh)
tallies_file.add_tally(tally)
# Instantiate a Tallies collection and export to XML
tallies_file = openmc.Tallies([tally])
tallies_file.export_to_xml()

49
examples/python/pincell/build-xml.py
View file

@ -11,7 +11,7 @@ particles = 1000
###############################################################################
# Exporting to OpenMC materials.xml File
# Exporting to OpenMC materials.xml file
###############################################################################
# Instantiate some Nuclides
@ -100,15 +100,14 @@ borated_water.add_nuclide(o16, 2.4672e-2)
borated_water.add_nuclide(o17, 6.0099e-5)
borated_water.add_s_alpha_beta('HH2O', '71t')
# Instantiate a MaterialsFile, register all Materials, and export to XML
materials_file = openmc.MaterialsFile()
# Instantiate a Materials collection and export to XML
materials_file = openmc.Materials([uo2, helium, zircaloy, borated_water])
materials_file.default_xs = '71c'
materials_file.add_materials([uo2, helium, zircaloy, borated_water])
materials_file.export_to_xml()
###############################################################################
# Exporting to OpenMC geometry.xml File
# Exporting to OpenMC geometry.xml file
###############################################################################
# Instantiate ZCylinder surfaces
@ -149,27 +148,26 @@ root = openmc.Universe(universe_id=0, name='root universe')
# Register Cells with Universe
root.add_cells([fuel, gap, clad, water])
# Instantiate a Geometry and register the root Universe
geometry = openmc.Geometry()
geometry.root_universe = root
# Instantiate a GeometryFile, register Geometry, and export to XML
geometry_file = openmc.GeometryFile()
geometry_file.geometry = geometry
geometry_file.export_to_xml()
# Instantiate a Geometry, register the root Universe, and export to XML
geometry = openmc.Geometry(root)
geometry.export_to_xml()
###############################################################################
# Exporting to OpenMC settings.xml File
# Exporting to OpenMC settings.xml file
###############################################################################
# Instantiate a SettingsFile, set all runtime parameters, and export to XML
settings_file = openmc.SettingsFile()
# Instantiate a Settings object, set all runtime parameters, and export to XML
settings_file = openmc.Settings()
settings_file.batches = batches
settings_file.inactive = inactive
settings_file.particles = particles
settings_file.set_source_space('box', [-0.62992, -0.62992, -1, \
0.62992, 0.62992, 1])
# Create an initial uniform spatial source distribution over fissionable zones
bounds = [-0.62992, -0.62992, -1, 0.62992, 0.62992, 1]
uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:], only_fissionable=True)
settings_file.source = openmc.source.Source(space=uniform_dist)
settings_file.entropy_lower_left = [-0.39218, -0.39218, -1.e50]
settings_file.entropy_upper_right = [0.39218, 0.39218, 1.e50]
settings_file.entropy_dimension = [10, 10, 1]
@ -177,7 +175,7 @@ settings_file.export_to_xml()
###############################################################################
# Exporting to OpenMC tallies.xml File
# Exporting to OpenMC tallies.xml file
###############################################################################
# Instantiate a tally mesh
@ -194,14 +192,9 @@ mesh_filter.mesh = mesh
# Instantiate the Tally
tally = openmc.Tally(tally_id=1, name='tally 1')
tally.add_filter(energy_filter)
tally.add_filter(mesh_filter)
tally.add_score('flux')
tally.add_score('fission')
tally.add_score('nu-fission')
tally.filters = [energy_filter, mesh_filter]
tally.scores = ['flux', 'fission', 'nu-fission']
# Instantiate a TalliesFile, register all Tallies, and export to XML
tallies_file = openmc.TalliesFile()
tallies_file.add_mesh(mesh)
tallies_file.add_tally(tally)
# Instantiate a Tallies collection and export to XML
tallies_file = openmc.Tallies([tally])
tallies_file.export_to_xml()

170
examples/python/pincell_multigroup/build-xml.py Normal file
View file

@ -0,0 +1,170 @@
import openmc
import openmc.mgxs
###############################################################################
# Simulation Input File Parameters
###############################################################################
# OpenMC simulation parameters
batches = 100
inactive = 10
particles = 1000
###############################################################################
# Exporting to OpenMC mgxs.xml file
###############################################################################
# Instantiate the energy group data
groups = openmc.mgxs.EnergyGroups(group_edges=[1E-11, 0.0635E-6, 10.0E-6,
1.0E-4, 1.0E-3, 0.5, 1.0, 20.0])
# Instantiate the 7-group (C5G7) cross section data
uo2_xsdata = openmc.XSdata('UO2.300K', groups)
uo2_xsdata.order = 0
uo2_xsdata.total = [0.1779492, 0.3298048, 0.4803882, 0.5543674,
0.3118013, 0.3951678, 0.5644058]
uo2_xsdata.absorption = [8.0248E-03, 3.7174E-03, 2.6769E-02, 9.6236E-02,
3.0020E-02, 1.1126E-01, 2.8278E-01]
uo2_xsdata.scatter = [[[0.1275370, 0.0423780, 0.0000094, 0.0000000, 0.0000000, 0.0000000, 0.0000000],
[0.0000000, 0.3244560, 0.0016314, 0.0000000, 0.0000000, 0.0000000, 0.0000000],
[0.0000000, 0.0000000, 0.4509400, 0.0026792, 0.0000000, 0.0000000, 0.0000000],
[0.0000000, 0.0000000, 0.0000000, 0.4525650, 0.0055664, 0.0000000, 0.0000000],
[0.0000000, 0.0000000, 0.0000000, 0.0001253, 0.2714010, 0.0102550, 0.0000000],
[0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0012968, 0.2658020, 0.0168090],
[0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0085458, 0.2730800]]]
uo2_xsdata.fission = [7.21206E-03, 8.19301E-04, 6.45320E-03,
1.85648E-02, 1.78084E-02, 8.30348E-02,
2.16004E-01]
uo2_xsdata.nu_fission = [2.005998E-02, 2.027303E-03, 1.570599E-02,
4.518301E-02, 4.334208E-02, 2.020901E-01,
5.257105E-01]
uo2_xsdata.chi = [5.8791E-01, 4.1176E-01, 3.3906E-04, 1.1761E-07,
0.0000E+00, 0.0000E+00, 0.0000E+00]
h2o_xsdata = openmc.XSdata('LWTR.300K', groups)
h2o_xsdata.order = 0
h2o_xsdata.total = [0.15920605, 0.412969593, 0.59030986, 0.58435,
0.718, 1.2544497, 2.650379]
h2o_xsdata.absorption = [6.0105E-04, 1.5793E-05, 3.3716E-04,
1.9406E-03, 5.7416E-03, 1.5001E-02,
3.7239E-02]
h2o_xsdata.scatter = [[[0.0444777, 0.1134000, 0.0007235, 0.0000037, 0.0000001, 0.0000000, 0.0000000],
[0.0000000, 0.2823340, 0.1299400, 0.0006234, 0.0000480, 0.0000074, 0.0000010],
[0.0000000, 0.0000000, 0.3452560, 0.2245700, 0.0169990, 0.0026443, 0.0005034],
[0.0000000, 0.0000000, 0.0000000, 0.0910284, 0.4155100, 0.0637320, 0.0121390],
[0.0000000, 0.0000000, 0.0000000, 0.0000714, 0.1391380, 0.5118200, 0.0612290],
[0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0022157, 0.6999130, 0.5373200],
[0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.1324400, 2.4807000]]]
mg_cross_sections_file = openmc.MGXSLibrary(groups)
mg_cross_sections_file.add_xsdatas([uo2_xsdata, h2o_xsdata])
mg_cross_sections_file.export_to_xml()
###############################################################################
# Exporting to OpenMC materials.xml file
###############################################################################
# Instantiate some Macroscopic Data
uo2_data = openmc.Macroscopic('UO2', '300K')
h2o_data = openmc.Macroscopic('LWTR', '300K')
# Instantiate some Materials and register the appropriate Macroscopic objects
uo2 = openmc.Material(material_id=1, name='UO2 fuel')
uo2.set_density('macro', 1.0)
uo2.add_macroscopic(uo2_data)
water = openmc.Material(material_id=2, name='Water')
water.set_density('macro', 1.0)
water.add_macroscopic(h2o_data)
# Instantiate a Materials collection and export to XML
materials_file = openmc.Materials([uo2, water])
materials_file.default_xs = '300K'
materials_file.export_to_xml()
###############################################################################
# Exporting to OpenMC geometry.xml file
###############################################################################
# Instantiate ZCylinder surfaces
fuel_or = openmc.ZCylinder(surface_id=1, x0=0, y0=0, R=0.54, name='Fuel OR')
left = openmc.XPlane(surface_id=4, x0=-0.63, name='left')
right = openmc.XPlane(surface_id=5, x0=0.63, name='right')
bottom = openmc.YPlane(surface_id=6, y0=-0.63, name='bottom')
top = openmc.YPlane(surface_id=7, y0=0.63, name='top')
left.boundary_type = 'reflective'
right.boundary_type = 'reflective'
top.boundary_type = 'reflective'
bottom.boundary_type = 'reflective'
# Instantiate Cells
fuel = openmc.Cell(cell_id=1, name='cell 1')
moderator = openmc.Cell(cell_id=2, name='cell 2')
# Use surface half-spaces to define regions
fuel.region = -fuel_or
moderator.region = +fuel_or & +left & -right & +bottom & -top
# Register Materials with Cells
fuel.fill = uo2
moderator.fill = water
# Instantiate Universe
root = openmc.Universe(universe_id=0, name='root universe')
# Register Cells with Universe
root.add_cells([fuel, moderator])
# Instantiate a Geometry, register the root Universe, and export to XML
geometry = openmc.Geometry(root)
geometry.export_to_xml()
###############################################################################
# Exporting to OpenMC settings.xml file
###############################################################################
# Instantiate a Settings object, set all runtime parameters, and export to XML
settings_file = openmc.Settings()
settings_file.energy_mode = "multi-group"
settings_file.cross_sections = "./mgxs.xml"
settings_file.batches = batches
settings_file.inactive = inactive
settings_file.particles = particles
# Create an initial uniform spatial source distribution over fissionable zones
bounds = [-0.63, -0.63, -1, 0.63, 0.63, 1]
uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:])
settings_file.source = openmc.source.Source(space=uniform_dist)
settings_file.export_to_xml()
###############################################################################
# Exporting to OpenMC tallies.xml file
###############################################################################
# Instantiate a tally mesh
mesh = openmc.Mesh(mesh_id=1)
mesh.type = 'regular'
mesh.dimension = [100, 100, 1]
mesh.lower_left = [-0.63, -0.63, -1.e50]
mesh.upper_right = [0.63, 0.63, 1.e50]
# Instantiate some tally Filters
energy_filter = openmc.Filter(type='energy',
bins=[1E-11, 0.0635E-6, 10.0E-6, 1.0E-4, 1.0E-3,
0.5, 1.0, 20.0])
mesh_filter = openmc.Filter()
mesh_filter.mesh = mesh
# Instantiate the Tally
tally = openmc.Tally(tally_id=1, name='tally 1')
tally.filters = [energy_filter, mesh_filter]
tally.scores = ['flux', 'fission', 'nu-fission']
# Instantiate a Tallies collection, register all Tallies, and export to XML
tallies_file = openmc.Tallies([tally])
tallies_file.export_to_xml()

34
examples/python/reflective/build-xml.py
View file

@ -1,5 +1,4 @@
import numpy as np
import openmc
###############################################################################
@ -13,7 +12,7 @@ particles = 10000
###############################################################################
# Exporting to OpenMC materials.xml File
# Exporting to OpenMC materials.xml file
###############################################################################
# Instantiate a Nuclides
@ -24,15 +23,14 @@ fuel = openmc.Material(material_id=1, name='fuel')
fuel.set_density('g/cc', 4.5)
fuel.add_nuclide(u235, 1.)
# Instantiate a MaterialsFile, register Material, and export to XML
materials_file = openmc.MaterialsFile()
# Instantiate a Materials collection and export to XML
materials_file = openmc.Materials([fuel])
materials_file.default_xs = '71c'
materials_file.add_material(fuel)
materials_file.export_to_xml()
###############################################################################
# Exporting to OpenMC geometry.xml File
# Exporting to OpenMC geometry.xml file
###############################################################################
# Instantiate Surfaces
@ -65,24 +63,24 @@ root = openmc.Universe(universe_id=0, name='root universe')
# Register Cell with Universe
root.add_cell(cell)
# Instantiate a Geometry and register the root Universe
geometry = openmc.Geometry()
geometry.root_universe = root
# Instantiate a GeometryFile, register Geometry, and export to XML
geometry_file = openmc.GeometryFile()
geometry_file.geometry = geometry
geometry_file.export_to_xml()
# Instantiate a Geometry, register the root Universe, and export to XML
geometry = openmc.Geometry(root)
geometry.export_to_xml()
###############################################################################
# Exporting to OpenMC settings.xml File
# Exporting to OpenMC settings.xml file
###############################################################################
# Instantiate a SettingsFile, set all runtime parameters, and export to XML
settings_file = openmc.SettingsFile()
# Instantiate a Settings object, set all runtime parameters, and export to XML
settings_file = openmc.Settings()
settings_file.batches = batches
settings_file.inactive = inactive
settings_file.particles = particles
settings_file.set_source_space('box', np.concatenate(cell.region.bounding_box))
# Create an initial uniform spatial source distribution over fissionable zones
uniform_dist = openmc.stats.Box(*cell.region.bounding_box,
only_fissionable=True)
settings_file.source = openmc.source.Source(space=uniform_dist)
settings_file.export_to_xml()

16
examples/xml/pincell_multigroup/geometry.xml Normal file
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@ -0,0 +1,16 @@
<geometry>
<surface coeffs="0. 0. 0.540" id="1" type="z-cylinder" />
<surface boundary="reflective" coeffs="-0.63" id="20" type="x-plane" />
<surface boundary="reflective" coeffs=" 0.63" id="21" type="x-plane" />
<surface boundary="reflective" coeffs="-0.63" id="22" type="y-plane" />
<surface boundary="reflective" coeffs=" 0.63" id="23" type="y-plane" />
<cell id="1" material="1" region=" -1" />
<cell id="2" material="7" region="1 20 -21 22 -23" />
</geometry>

54
examples/xml/pincell_multigroup/materials.xml Normal file
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@ -0,0 +1,54 @@
<?xml version="1.0"?>
<materials>
<!-- Set default xs set to use 300K data -->
<default_xs>300K</default_xs>
<!-- UO2 -->
<material id="1">
<density units="macro" value="1.0" />
<macroscopic name="UO2"/>
</material>
<!-- 4.3% MOX -->
<material id="2">
<density units="macro" value="1.0" />
<macroscopic name="MOX1"/>
</material>
<!-- 7.0 MOX -->
<material id="3">
<density units="macro" value="1.0" />
<macroscopic name="MOX2"/>
</material>
<!-- 8.0% MOX -->
<material id="4">
<density units="macro" value="1.0" />
<macroscopic name="MOX3"/>
</material>
<!-- Fission Chamber -->
<material id="5">
<density units="macro" value="1.0" />
<macroscopic name="FC"/>
</material>
<!-- Guide Tube -->
<material id="6">
<density units="macro" value="1.0" />
<macroscopic name="GT"/>
</material>
<!-- Water -->
<material id="7">
<density units="macro" value="1.0" />
<macroscopic name="LWTR"/>
</material>
<!-- Control Rod -->
<material id="8">
<density units="macro" value="1.0" />
<macroscopic name="CR"/>
</material>
</materials>

383
examples/xml/pincell_multigroup/mg_cross_sections.xml Normal file
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@ -0,0 +1,383 @@
<?xml version="1.0"?>
<library>
<!-- Before getting to the data, set common information -->
<groups> 7 </groups>
<group_structure>
1E-11 0.0635E-6 10.0E-6 1.0E-4 1.0E-3 0.5 1.0 20.0
</group_structure>
<!--
Move on to the data. Each <xsdata> has a unique id and label.
-->
<xsdata>
<!-- Meta data for this data -->
<name>UO2.300K</name>
<alias>UO2.300K</alias>
<kT> 2.53E-8 </kT> <!-- in MeV -->
<order>0</order>
<fissionable>true</fissionable>
<!-- Optional (default is isotropic) -->
<representation>isotropic</representation>
<!-- The data itself, like tallies,
goes from low energies (groups) to high energies
-->
<absorption>
8.0248E-03 3.7174E-03 2.6769E-02 9.6236E-02 3.0020E-02 1.1126E-01 2.8278E-01
</absorption>
<nu_fission>
2.005998E-02 2.027303E-03 1.570599E-02 4.518301E-02 4.334208E-02 2.020901E-01 5.257105E-01
</nu_fission>
<chi>
5.8791E-01 4.1176E-01 3.3906E-04 1.1761E-07 0.0000E+00 0.0000E+00 0.0000E+00
</chi>
<fission>
7.21206E-03 8.19301E-04 6.45320E-03 1.85648E-02 1.78084E-02 8.30348E-02 2.16004E-01
</fission>
<!-- units of MeV/cm -->
<!-- If no kappa fission tallies, this is not needed; it will not be loaded
if there is no kappa fission scores anyways -->
<k_fission>
1.0 1.0 1.0 1.0 1.0 1.0 1.0
</k_fission>
<!-- for consistency must include nu-scatter -->
<!-- will be a matrix of (order+1) x g_in x g_out -->
<scatter>
0.1275370 0.0423780 0.0000094 0.0000000 0.0000000 0.0000000 0.0000000
0.0000000 0.3244560 0.0016314 0.0000000 0.0000000 0.0000000 0.0000000
0.0000000 0.0000000 0.4509400 0.0026792 0.0000000 0.0000000 0.0000000
0.0000000 0.0000000 0.0000000 0.4525650 0.0055664 0.0000000 0.0000000
0.0000000 0.0000000 0.0000000 0.0001253 0.2714010 0.0102550 0.0000000
0.0000000 0.0000000 0.0000000 0.0000000 0.0012968 0.2658020 0.0168090
0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0085458 0.2730800
</scatter>
<!-- If total is not provided, it will be calculated.
However, in the C5G7 problems, we want to use a transport-corrected value
so we dont want to have it be calculated -->
<total>
0.1779492 0.3298048 0.4803882 0.5543674000000001 0.3118013 0.39516779999999996 0.5644058
</total>
</xsdata>
<xsdata>
<!-- Meta data for this data -->
<name>MOX1.300K</name>
<alias>MOX1.300K</alias>
<kT> 2.53E-8 </kT> <!-- in MeV -->
<order>0</order>
<fissionable>true</fissionable>
<!-- The data itself, like tallies,
goes from low energies (groups) to high energies
-->
<absorption>
8.4339E-03 3.7577E-03 2.7970E-02 1.0421E-01 1.3994E-01 4.0918E-01 4.0935E-01
</absorption>
<!--
Since chi_vector is false, this will be a matrix
Matrix is g_in, g_out.
This is to show that you can either use a chi vector + nu_fission vector,
like in the UO2 data, or a nu_fission matrix like here.
-->
<nu_fission>
1.27888062E-02 8.95701528E-03 7.37557218E-06 2.55837033E-09 0.00000000E+00 0.00000000E+00 0.00000000E+00
1.49041240E-03 1.04385401E-03 8.59552023E-07 2.98153464E-10 0.00000000E+00 0.00000000E+00 0.00000000E+00
9.56411400E-03 6.69850756E-03 5.51582469E-06 1.91327830E-09 0.00000000E+00 0.00000000E+00 0.00000000E+00
3.84928781E-02 2.69596154E-02 2.21996483E-05 7.70040890E-09 0.00000000E+00 0.00000000E+00 0.00000000E+00
1.80629998E-02 1.26509513E-02 1.04173100E-05 3.61346022E-09 0.00000000E+00 0.00000000E+00 0.00000000E+00
3.91930789E-01 2.74500216E-01 2.26034688E-04 7.84048241E-08 0.00000000E+00 0.00000000E+00 0.00000000E+00
4.19762096E-01 2.93992687E-01 2.42085585E-04 8.39724109E-08 0.00000000E+00 0.00000000E+00 0.00000000E+00
</nu_fission>
<fission>
7.62704E-03 8.76898E-04 5.69835E-03 2.28872E-02 1.07635E-02 2.32757E-01 2.48968E-01
</fission>
<!-- units of MeV/cm -->
<k_fission>
1.0 1.0 1.0 1.0 1.0 1.0 1.0
</k_fission>
<!-- for consistency must include nu-scatter -->
<!-- will be a matrix of (order+1) x g_in x g_out -->
<scatter>
1.27537000E-01 4.23780000E-02 9.43740000E-06 5.51630000E-09 0.00000000E+00 0.00000000E+00 0.00000000E+00
0.00000000E+00 3.24456000E-01 1.63140000E-03 3.14270000E-09 0.00000000E+00 0.00000000E+00 0.00000000E+00
0.00000000E+00 0.00000000E+00 4.50940000E-01 2.67920000E-03 0.00000000E+00 0.00000000E+00 0.00000000E+00
0.00000000E+00 0.00000000E+00 0.00000000E+00 4.52565000E-01 5.56640000E-03 0.00000000E+00 0.00000000E+00
0.00000000E+00 0.00000000E+00 0.00000000E+00 1.25250000E-04 2.71401000E-01 1.02550000E-02 1.00210000E-08
0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 1.29680000E-03 2.65802000E-01 1.68090000E-02
0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 8.54580000E-03 2.73080000E-01
</scatter>
<total>
0.1783583429163 0.3298451031427 0.4815892 0.5623414 0.421721260021 0.6930878 0.6909757999999999
</total>
</xsdata>
<xsdata>
<!-- Meta data for this data -->
<name>MOX2.300K</name>
<alias>MOX2.300K</alias>
<kT> 2.53E-8 </kT> <!-- in MeV -->
<order>0</order>
<fissionable>true</fissionable>
<!-- The data itself, like tallies,
goes from low energies (groups) to high energies
-->
<absorption>
0.0090657 0.0042967 0.032881 0.12203 0.18298 0.56846 0.58521
</absorption>
<!--
Since chi_vector is false, this will be a matrix
Matrix is g_in, g_out !!! Need to get these values looking right to match
output of a nu-fission tally with <energy> filter above <energyout> filter
-->
<nu_fission>
1.40004593E-02 9.80563205E-03 8.07435789E-06 2.80075866E-09 0.00000000E+00 0.00000000E+00 0.00000000E+00
2.26856185E-03 1.58885378E-03 1.30832709E-06 4.53820413E-10 0.00000000E+00 0.00000000E+00 0.00000000E+00
1.41886199E-02 9.93741584E-03 8.18287404E-06 2.83839974E-09 0.00000000E+00 0.00000000E+00 0.00000000E+00
5.54788444E-02 3.88562347E-02 3.19958106E-05 1.10984111E-08 0.00000000E+00 0.00000000E+00 0.00000000E+00
2.69085702E-02 1.88462058E-02 1.55187355E-05 5.38299559E-09 0.00000000E+00 0.00000000E+00 0.00000000E+00
5.45687127E-01 3.82187973E-01 3.14709185E-04 1.09163414E-07 0.00000000E+00 0.00000000E+00 0.00000000E+00
6.13307712E-01 4.29548032E-01 3.53707392E-04 1.22690752E-07 0.00000000E+00 0.00000000E+00 0.00000000E+00
</nu_fission>
<fission>
0.00825446 0.00132565 0.00842156 0.032873 0.0159636 0.323794 0.362803
</fission>
<!-- units of MeV/cm -->
<k_fission>
1.0 1.0 1.0 1.0 1.0 1.0 1.0
</k_fission>
<!-- for consistency must include nu-scatter -->
<!-- will be a matrix of (order+1) x g_in x g_out -->
<scatter>
1.30457000E-01 4.17920000E-02 8.51050000E-06 5.13290000E-09 0.00000000E+00 0.00000000E+00 0.00000000E+00
0.00000000E+00 3.28428000E-01 1.64360000E-03 2.20170000E-09 0.00000000E+00 0.00000000E+00 0.00000000E+00
0.00000000E+00 0.00000000E+00 4.58371000E-01 2.53310000E-03 0.00000000E+00 0.00000000E+00 0.00000000E+00
0.00000000E+00 0.00000000E+00 0.00000000E+00 4.63709000E-01 5.47660000E-03 0.00000000E+00 0.00000000E+00
0.00000000E+00 0.00000000E+00 0.00000000E+00 1.76190000E-04 2.82313000E-01 8.72890000E-03 9.00160000E-09
0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 2.27600000E-03 2.49751000E-01 1.31140000E-02
0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 8.86450000E-03 2.59529000E-01
</scatter>
<total>
0.1813232156329 0.3343683022017 0.4937851 0.5912156 0.47419809900160004 0.833601 0.8536035
</total>
</xsdata>
<xsdata>
<!-- Meta data for this data -->
<name>MOX3.300K</name>
<alias>MOX3.300K</alias>
<kT> 2.53E-8 </kT> <!-- in MeV -->
<order>0</order>
<fissionable>true</fissionable>
<!-- The data itself, like tallies,
goes from low energies (groups) to high energies
-->
<absorption>
9.48620000E-03 4.65560000E-03 3.62400000E-02 1.32720000E-01 2.08400000E-01 6.58700000E-01 6.90170000E-01
</absorption>
<!--
Since chi_vector is false, this will be a matrix
Matrix is g_in, g_out !!! Need to get these values looking right to match
output of a nu-fission tally with <energy> filter above <energyout> filter
-->
<nu_fission>
1.48071013E-02 1.03705874E-02 8.53956516E-06 2.96212546E-09 0.00000000E+00 0.00000000E+00 0.00000000E+00
2.78640474E-03 1.95154023E-03 1.60697792E-06 5.57413653E-10 0.00000000E+00 0.00000000E+00 0.00000000E+00
1.73304404E-02 1.21378819E-02 9.99482763E-06 3.46691346E-09 0.00000000E+00 0.00000000E+00 0.00000000E+00
6.59928975E-02 4.62200600E-02 3.80594850E-05 1.32017225E-08 0.00000000E+00 0.00000000E+00 0.00000000E+00
3.25131926E-02 2.27715674E-02 1.87510386E-05 6.50418701E-09 0.00000000E+00 0.00000000E+00 0.00000000E+00
6.32002662E-01 4.42641588E-01 3.64489161E-04 1.26430632E-07 0.00000000E+00 0.00000000E+00 0.00000000E+00
7.28595687E-01 5.10293344E-01 4.20196380E-04 1.45753838E-07 0.00000000E+00 0.00000000E+00 0.00000000E+00
</nu_fission>
<fission>
8.67209000E-03 1.62426000E-03 1.02716000E-02 3.90447000E-02 1.92576000E-02 3.74888000E-01 4.30599000E-01
</fission>
<!-- units of MeV/cm -->
<k_fission>
1.0 1.0 1.0 1.0 1.0 1.0 1.0
</k_fission>
<!-- for consistency must include nu-scatter -->
<!-- will be a matrix of (order+1) x g_in x g_out -->
<scatter>
1.31504000E-01 4.20460000E-02 8.69720000E-06 5.19380000E-09 0.00000000E+00 0.00000000E+00 0.00000000E+00
0.00000000E+00 3.30403000E-01 1.64630000E-03 2.60060000E-09 0.00000000E+00 0.00000000E+00 0.00000000E+00
0.00000000E+00 0.00000000E+00 4.61792000E-01 2.47490000E-03 0.00000000E+00 0.00000000E+00 0.00000000E+00
0.00000000E+00 0.00000000E+00 0.00000000E+00 4.68021000E-01 5.43300000E-03 0.00000000E+00 0.00000000E+00
0.00000000E+00 0.00000000E+00 0.00000000E+00 1.85970000E-04 2.85771000E-01 8.39730000E-03 8.92800000E-09
0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 2.39160000E-03 2.47614000E-01 1.23220000E-02
0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 8.96810000E-03 2.56093000E-01
</scatter>
<total>
1.83044902E-01 3.36704903E-01 5.00506900E-01 6.06174000E-01 5.02754279E-01 9.21027600E-01 9.55231100E-01
</total>
</xsdata>
<xsdata>
<!-- Meta data for this data -->
<name>FC.300K</name>
<alias>FC.300K</alias>
<kT> 2.53E-8 </kT> <!-- in MeV -->
<order>0</order>
<fissionable>true</fissionable>
<!-- The data itself, like tallies,
goes from low energies (groups) to high energies
-->
<absorption>
5.1132E-04 7.5813E-05 3.1643E-04 1.1675E-03 3.3977E-03 9.1886E-03 2.3244E-02
</absorption>
<nu_fission>
1.323401E-08 1.434500E-08 1.128599E-06 1.276299E-05 3.538502E-07 1.740099E-06 5.063302E-06
</nu_fission>
<chi>
5.8791E-01 4.1176E-01 3.3906E-04 1.1761E-07 0.0000E+00 0.0000E+00 0.0000E+00
</chi>
<fission>
4.79002E-09 5.82564E-09 4.63719E-07 5.24406E-06 1.45390E-07 7.14972E-07 2.08041E-06
</fission>
<!-- units of MeV/cm -->
<k_fission>
1.0 1.0 1.0 1.0 1.0 1.0 1.0
</k_fission>
<!-- for consistency must include nu-scatter -->
<!-- will be a matrix of (order+1) x g_in x g_out -->
<scatter>
6.61659000E-02 5.90700000E-02 2.83340000E-04 1.46220000E-06 2.06420000E-08 0.00000000E00 0.00000000E00
0.00000000E00 2.40377000E-01 5.24350000E-02 2.49900000E-04 1.92390000E-05 2.98750000E-06 4.21400000E-07
0.00000000E00 0.00000000E00 1.83425000E-01 9.22880000E-02 6.93650000E-03 1.07900000E-03 2.05430000E-04
0.00000000E00 0.00000000E00 0.00000000E00 7.90769000E-02 1.69990000E-01 2.58600000E-02 4.92560000E-03
0.00000000E00 0.00000000E00 0.00000000E00 3.73400000E-05 9.97570000E-02 2.06790000E-01 2.44780000E-02
0.00000000E00 0.00000000E00 0.00000000E00 0.00000000E00 9.17420000E-04 3.16774000E-01 2.38760000E-01
0.00000000E00 0.00000000E00 0.00000000E00 0.00000000E00 0.00000000E00 4.97930000E-02 1.09910000E00
</scatter>
<total>
1.26032048E-01 2.93160367E-01 2.84250824E-01 2.81025244E-01 3.34460185E-01 5.65640735E-01 1.17213908E00
</total>
</xsdata>
<xsdata>
<!-- Meta data for this data -->
<name>GT.300K</name>
<alias>GT.300K</alias>
<kT> 2.53E-8 </kT> <!-- in MeV -->
<order>0</order>
<fissionable>false</fissionable>
<!-- The data itself, like tallies,
goes from low energies (groups) to high energies
-->
<absorption>
5.11320000E-04 7.58010000E-05 3.15720000E-04 1.15820000E-03 3.39750000E-03 9.18780000E-03 2.32420000E-02
</absorption>
<!-- for consistency must include nu-scatter -->
<!-- will be a matrix of (order+1) x g_in x g_out -->
<scatter>
6.61659000E-02 5.90700000E-02 2.83340000E-04 1.46220000E-06 2.06420000E-08 0.00000000E+00 0.00000000E+00
0.00000000E+00 2.40377000E-01 5.24350000E-02 2.49900000E-04 1.92390000E-05 2.98750000E-06 4.21400000E-07
0.00000000E+00 0.00000000E+00 1.83297000E-01 9.23970000E-02 6.94460000E-03 1.08030000E-03 2.05670000E-04
0.00000000E+00 0.00000000E+00 0.00000000E+00 7.88511000E-02 1.70140000E-01 2.58810000E-02 4.92970000E-03
0.00000000E+00 0.00000000E+00 0.00000000E+00 3.73330000E-05 9.97372000E-02 2.06790000E-01 2.44780000E-02
0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 9.17260000E-04 3.16765000E-01 2.38770000E-01
0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 4.97920000E-02 1.09912000E+00
</scatter>
<total>
1.26032043E-01 2.93160349E-01 2.84240290E-01 2.80960000E-01 3.34440033E-01 5.65640060E-01 1.17215400E+00
</total>
</xsdata>
<xsdata>
<!-- Meta data for this data -->
<name>LWTR.300K</name>
<alias>LWTR.300K</alias>
<kT> 2.53E-8 </kT> <!-- in MeV -->
<order>0</order>
<fissionable>false</fissionable>
<!-- The data itself, like tallies,
goes from low energies (groups) to high energies
-->
<absorption>
6.0105E-04 1.5793E-05 3.3716E-04 1.9406E-03 5.7416E-03 1.5001E-02 3.7239E-02
</absorption>
<!-- for consistency must include nu-scatter -->
<!-- will be a matrix of (order+1) x g_in x g_out -->
<scatter>
0.0444777 0.1134000 0.0007235 0.0000037 0.0000001 0.0000000 0.0000000
0.0000000 0.2823340 0.1299400 0.0006234 0.0000480 0.0000074 0.0000010
0.0000000 0.0000000 0.3452560 0.2245700 0.0169990 0.0026443 0.0005034
0.0000000 0.0000000 0.0000000 0.0910284 0.4155100 0.0637320 0.0121390
0.0000000 0.0000000 0.0000000 0.0000714 0.1391380 0.5118200 0.0612290
0.0000000 0.0000000 0.0000000 0.0000000 0.0022157 0.6999130 0.5373200
0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.1324400 2.4807000
</scatter>
<total>
0.15920605 0.41296959299999997 0.59030986 0.5843499999999999 0.7180000000000001 1.2544497000000001 2.650379
</total>
</xsdata>
<xsdata>
<!-- Meta data for this data -->
<name>CR.300K</name>
<alias>CR.300K</alias>
<kT> 2.53E-8 </kT> <!-- in MeV -->
<order>0</order>
<fissionable>false</fissionable>
<!-- The data itself, like tallies,
goes from low energies (groups) to high energies
-->
<absorption>
1.70490000E-03 8.36224000E-03 8.37901000E-02 3.97797000E-01 6.98763000E-01 9.29508000E-01 1.17836000E+00
</absorption>
<!-- for consistency must include nu-scatter -->
<!-- will be a matrix of (order+1) x g_in x g_out -->
<scatter>
1.70563000E-01 4.44012000E-02 9.83670000E-05 1.27786000E-07 0.00000000E+00 0.00000000E+00 0.00000000E+00
0.00000000E+00 4.71050000E-01 6.85480000E-04 3.91395000E-10 0.00000000E+00 0.00000000E+00 0.00000000E+00
0.00000000E+00 0.00000000E+00 8.01859000E-01 7.20132000E-04 0.00000000E+00 0.00000000E+00 0.00000000E+00
0.00000000E+00 0.00000000E+00 0.00000000E+00 5.70752000E-01 1.46015000E-03 0.00000000E+00 0.00000000E+00
0.00000000E+00 0.00000000E+00 0.00000000E+00 6.55562000E-05 2.07838000E-01 3.81486000E-03 3.69760000E-09
0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 1.02427000E-03 2.02465000E-01 4.75290000E-03
0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 0.00000000E+00 3.53043000E-03 6.58597000E-01
</scatter>
<total>
2.16767595E-01 4.80097720E-01 8.86369232E-01 9.70009150E-01 9.10481420E-01 1.13775017E+00 1.84048743E+00
</total>
</xsdata>
</library>

28
examples/xml/pincell_multigroup/plots.xml Normal file
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@ -0,0 +1,28 @@
<?xml version="1.0"?>
<plots>
<plot>
<id>1</id>
<filename>mat</filename>
<color>material</color>
<origin>0 0 0</origin>
<width>1.26 1.26</width>
<type>slice</type>
<pixels>1000 1000 </pixels>
<col_spec id="1" rgb="255 0 0" />
<col_spec id="2" rgb="0 0 0" />
<col_spec id="3" rgb="0 255 0" />
<col_spec id="4" rgb="0 0 255" />
</plot>
<plot>
<id>2</id>
<filename>cell</filename>
<color>cell</color>
<origin>0 0 0</origin>
<width>1.26 1.26</width>
<type>slice</type>
<pixels>1000 1000 </pixels>
</plot>
</plots>

40
examples/xml/pincell_multigroup/settings.xml Normal file
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@ -0,0 +1,40 @@
<?xml version="1.0"?>
<settings>
<energy_mode>multi-group</energy_mode>
<!--
Define how many particles to run and for how many batches
in an eigenvalue calculation mode
-->
<eigenvalue>
<batches>100</batches>
<inactive>10</inactive>
<particles>1000</particles>
</eigenvalue>
<!--
Start with uniformally distributed neutron source
with the default energy spectrum of a Maxwellian
and isotropic distribution.
-->
<source>
<space type="box">
<parameters>
-0.63 -0.63 -1E50
0.63 0.63 1E50
</parameters>
</space>
</source>
<output>
<cross_sections>true</cross_sections>
<summary>true</summary>
<tallies>true</tallies>
</output>
<survival_biasing>false</survival_biasing>
<cross_sections>./mg_cross_sections.xml</cross_sections>
</settings>

13
examples/xml/pincell_multigroup/tallies.xml Normal file
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@ -0,0 +1,13 @@
<?xml version="1.0"?>
<tallies>
<mesh id="1" type="regular">
<dimension>100 100 1</dimension>
<lower_left>-0.63 -0.63 -1e+50</lower_left>
<upper_right>0.63 0.63 1e+50</upper_right>
</mesh>
<tally id="1" name="tally 1">
<filter bins="1e-11 6.35e-08 1e-05 0.0001 0.001 0.5 1.0 20.0" type="energy" />
<filter bins="1" type="mesh" />
<scores>flux fission nu-fission</scores>
</tally>
</tallies>

2
man/man1/openmc.1
View file

@ -46,7 +46,7 @@ to locate ACE format cross section libraries if the user has not specified the
<cross_sections> tag in
.I settings.xml\fP.
.SH LICENSE
Copyright \(co 2011-2015 Massachusetts Institute of Technology.
Copyright \(co 2011-2016 Massachusetts Institute of Technology.
.PP
Permission is hereby granted, free of charge, to any person obtaining a copy of
this software and associated documentation files (the "Software"), to deal in

7
openmc/__init__.py
View file

@ -1,11 +1,15 @@
from openmc.cell import *
from openmc.lattice import *
from openmc.element import *
from openmc.geometry import *
from openmc.nuclide import *
from openmc.macroscopic import *
from openmc.material import *
from openmc.plots import *
from openmc.settings import *
from openmc.surface import *
from openmc.universe import *
from openmc.mgxs_library import *
from openmc.mesh import *
from openmc.filter import *
from openmc.trigger import *
@ -14,6 +18,9 @@ from openmc.cmfd import *
from openmc.executor import *
from openmc.statepoint import *
from openmc.summary import *
from openmc.region import *
from openmc.source import *
from openmc.particle_restart import *
try:
from openmc.opencg_compatible import *

868
openmc/arithmetic.py Normal file
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@ -0,0 +1,868 @@
import sys
import copy
from collections import Iterable
import numpy as np
from openmc import Filter, Nuclide
from openmc.filter import _FILTER_TYPES
import openmc.checkvalue as cv
if sys.version_info[0] >= 3:
basestring = str
# Acceptable tally arithmetic binary operations
_TALLY_ARITHMETIC_OPS = ['+', '-', '*', '/', '^']
# Acceptable tally aggregation operations
_TALLY_AGGREGATE_OPS = ['sum', 'avg']
class CrossScore(object):
"""A special-purpose tally score used to encapsulate all combinations of two
tally's scores as an outer product for tally arithmetic.
Parameters
----------
left_score : str or CrossScore
The left score in the outer product
right_score : str or CrossScore
The right score in the outer product
binary_op : str
The tally arithmetic binary operator (e.g., '+', '-', etc.) used to
combine two tally's scores with this CrossNuclide
Attributes
----------
left_score : str or CrossScore
The left score in the outer product
right_score : str or CrossScore
The right score in the outer product
binary_op : str
The tally arithmetic binary operator (e.g., '+', '-', etc.) used to
combine two tally's scores with this CrossScore
"""
def __init__(self, left_score=None, right_score=None, binary_op=None):
self._left_score = None
self._right_score = None
self._binary_op = None
if left_score is not None:
self.left_score = left_score
if right_score is not None:
self.right_score = right_score
if binary_op is not None:
self.binary_op = binary_op
def __hash__(self):
return hash(repr(self))
def __eq__(self, other):
return str(other) == str(self)
def __ne__(self, other):
return not self == other
def __repr__(self):
string = '({0} {1} {2})'.format(self.left_score,
self.binary_op, self.right_score)
return string
@property
def left_score(self):
return self._left_score
@property
def right_score(self):
return self._right_score
@property
def binary_op(self):
return self._binary_op
@left_score.setter
def left_score(self, left_score):
cv.check_type('left_score', left_score,
(basestring, CrossScore, AggregateScore))
self._left_score = left_score
@right_score.setter
def right_score(self, right_score):
cv.check_type('right_score', right_score,
(basestring, CrossScore, AggregateScore))
self._right_score = right_score
@binary_op.setter
def binary_op(self, binary_op):
cv.check_type('binary_op', binary_op, basestring)
cv.check_value('binary_op', binary_op, _TALLY_ARITHMETIC_OPS)
self._binary_op = binary_op
class CrossNuclide(object):
"""A special-purpose nuclide used to encapsulate all combinations of two
tally's nuclides as an outer product for tally arithmetic.
Parameters
----------
left_nuclide : Nuclide or CrossNuclide
The left nuclide in the outer product
right_nuclide : Nuclide or CrossNuclide
The right nuclide in the outer product
binary_op : str
The tally arithmetic binary operator (e.g., '+', '-', etc.) used to
combine two tally's nuclides with this CrossNuclide
Attributes
----------
left_nuclide : Nuclide or CrossNuclide
The left nuclide in the outer product
right_nuclide : Nuclide or CrossNuclide
The right nuclide in the outer product
binary_op : str
The tally arithmetic binary operator (e.g., '+', '-', etc.) used to
combine two tally's nuclides with this CrossNuclide
"""
def __init__(self, left_nuclide=None, right_nuclide=None, binary_op=None):
self._left_nuclide = None
self._right_nuclide = None
self._binary_op = None
if left_nuclide is not None:
self.left_nuclide = left_nuclide
if right_nuclide is not None:
self.right_nuclide = right_nuclide
if binary_op is not None:
self.binary_op = binary_op
def __hash__(self):
return hash(repr(self))
def __eq__(self, other):
return str(other) == str(self)
def __ne__(self, other):
return not self == other
def __repr__(self):
return self.name
@property
def left_nuclide(self):
return self._left_nuclide
@property
def right_nuclide(self):
return self._right_nuclide
@property
def binary_op(self):
return self._binary_op
@property
def name(self):
string = ''
# If the Summary was linked, the left nuclide is a Nuclide object
if isinstance(self.left_nuclide, Nuclide):
string += '(' + self.left_nuclide.name
# If the Summary was not linked, the left nuclide is the ZAID
else:
string += '(' + str(self.left_nuclide)
string += ' ' + self.binary_op + ' '
# If the Summary was linked, the right nuclide is a Nuclide object
if isinstance(self.right_nuclide, Nuclide):
string += self.right_nuclide.name + ')'
# If the Summary was not linked, the right nuclide is the ZAID
else:
string += str(self.right_nuclide) + ')'
return string
@left_nuclide.setter
def left_nuclide(self, left_nuclide):
cv.check_type('left_nuclide', left_nuclide,
(Nuclide, CrossNuclide, AggregateNuclide))
self._left_nuclide = left_nuclide
@right_nuclide.setter
def right_nuclide(self, right_nuclide):
cv.check_type('right_nuclide', right_nuclide,
(Nuclide, CrossNuclide, AggregateNuclide))
self._right_nuclide = right_nuclide
@binary_op.setter
def binary_op(self, binary_op):
cv.check_type('binary_op', binary_op, basestring)
cv.check_value('binary_op', binary_op, _TALLY_ARITHMETIC_OPS)
self._binary_op = binary_op
class CrossFilter(object):
"""A special-purpose filter used to encapsulate all combinations of two
tally's filter bins as an outer product for tally arithmetic.
Parameters
----------
left_filter : Filter or CrossFilter
The left filter in the outer product
right_filter : Filter or CrossFilter
The right filter in the outer product
binary_op : str
The tally arithmetic binary operator (e.g., '+', '-', etc.) used to
combine two tally's filter bins with this CrossFilter
Attributes
----------
type : str
The type of the crossfilter (e.g., 'energy / energy')
left_filter : Filter or CrossFilter
The left filter in the outer product
right_filter : Filter or CrossFilter
The right filter in the outer product
binary_op : str
The tally arithmetic binary operator (e.g., '+', '-', etc.) used to
combine two tally's filter bins with this CrossFilter
bins : dict of Iterable
A dictionary of the bins from each filter keyed by the types of the
left / right filters
num_bins : Integral
The number of filter bins (always 1 if aggregate_filter is defined)
stride : Integral
The number of filter, nuclide and score bins within each of this
crossfilter's bins.
"""
def __init__(self, left_filter=None, right_filter=None, binary_op=None):
left_type = left_filter.type
right_type = right_filter.type
self._type = '({0} {1} {2})'.format(left_type, binary_op, right_type)
self._bins = {}
self._stride = None
self._left_filter = None
self._right_filter = None
self._binary_op = None
if left_filter is not None:
self.left_filter = left_filter
self._bins['left'] = left_filter.bins
if right_filter is not None:
self.right_filter = right_filter
self._bins['right'] = right_filter.bins
if binary_op is not None:
self.binary_op = binary_op
def __hash__(self):
return hash((self.left_filter, self.right_filter))
def __eq__(self, other):
return str(other) == str(self)
def __ne__(self, other):
return not self == other
def __repr__(self):
string = 'CrossFilter\n'
filter_type = '({0} {1} {2})'.format(self.left_filter.type,
self.binary_op,
self.right_filter.type)
filter_bins = '({0} {1} {2})'.format(self.left_filter.bins,
self.binary_op,
self.right_filter.bins)
string += '{0: <16}{1}{2}\n'.format('\tType', '=\t', filter_type)
string += '{0: <16}{1}{2}\n'.format('\tBins', '=\t', filter_bins)
return string
@property
def left_filter(self):
return self._left_filter
@property
def right_filter(self):
return self._right_filter
@property
def binary_op(self):
return self._binary_op
@property
def type(self):
return self._type
@property
def bins(self):
return self._bins['left'], self._bins['right']
@property
def num_bins(self):
if self.left_filter is not None and self.right_filter is not None:
return self.left_filter.num_bins * self.right_filter.num_bins
else:
return 0
@property
def stride(self):
return self._stride
@type.setter
def type(self, filter_type):
if filter_type not in _FILTER_TYPES:
msg = 'Unable to set CrossFilter type to "{0}" since it ' \
'is not one of the supported types'.format(filter_type)
raise ValueError(msg)
self._type = filter_type
@left_filter.setter
def left_filter(self, left_filter):
cv.check_type('left_filter', left_filter,
(Filter, CrossFilter, AggregateFilter))
self._left_filter = left_filter
self._bins['left'] = left_filter.bins
@right_filter.setter
def right_filter(self, right_filter):
cv.check_type('right_filter', right_filter,
(Filter, CrossFilter, AggregateFilter))
self._right_filter = right_filter
self._bins['right'] = right_filter.bins
@binary_op.setter
def binary_op(self, binary_op):
cv.check_type('binary_op', binary_op, basestring)
cv.check_value('binary_op', binary_op, _TALLY_ARITHMETIC_OPS)
self._binary_op = binary_op
@stride.setter
def stride(self, stride):
self._stride = stride
def get_bin_index(self, filter_bin):
"""Returns the index in the CrossFilter for some bin.
Parameters
----------
filter_bin : 2-tuple
A 2-tuple where each value corresponds to the bin of interest
in the left and right filter, respectively. A bin is the integer
ID for 'material', 'surface', 'cell', 'cellborn', and 'universe'
Filters. The bin is an integer for the cell instance ID for
'distribcell' Filters. The bin is a 2-tuple of floats for 'energy'
and 'energyout' filters corresponding to the energy boundaries of
the bin of interest. The bin is a (x,y,z) 3-tuple for 'mesh'
filters corresponding to the mesh cell of interest.
Returns
-------
filter_index : Integral
The index in the Tally data array for this filter bin.
"""
left_index = self.left_filter.get_bin_index(filter_bin[0])
right_index = self.right_filter.get_bin_index(filter_bin[0])
filter_index = left_index * self.right_filter.num_bins + right_index
return filter_index
def get_pandas_dataframe(self, data_size, summary=None):
"""Builds a Pandas DataFrame for the CrossFilter's bins.
This method constructs a Pandas DataFrame object for the CrossFilter
with columns annotated by filter bin information. This is a helper
method for the Tally.get_pandas_dataframe(...) method. This method
recursively builds and concatenates Pandas DataFrames for the left
and right filters and crossfilters.
This capability has been tested for Pandas >=0.13.1. However, it is
recommended to use v0.16 or newer versions of Pandas since this method
uses Pandas' Multi-index functionality.
Parameters
----------
data_size : Integral
The total number of bins in the tally corresponding to this filter
summary : None or Summary
An optional Summary object to be used to construct columns for
distribcell tally filters (default is None). The geometric
information in the Summary object is embedded into a Multi-index
column with a geometric "path" to each distribcell instance.
NOTE: This option requires the OpenCG Python package.
Returns
-------
pandas.DataFrame
A Pandas DataFrame with columns of strings that characterize the
crossfilter's bins. Each entry in the DataFrame will include one
or more binary operations used to construct the crossfilter's bins.
The number of rows in the DataFrame is the same as the total number
of bins in the corresponding tally, with the filter bins
appropriately tiled to map to the corresponding tally bins.
See also
--------
Tally.get_pandas_dataframe(), Filter.get_pandas_dataframe()
"""
# If left and right filters are identical, do not combine bins
if self.left_filter == self.right_filter:
df = self.left_filter.get_pandas_dataframe(data_size, summary)
# If left and right filters are different, combine their bins
else:
left_df = self.left_filter.get_pandas_dataframe(data_size, summary)
right_df = self.right_filter.get_pandas_dataframe(data_size, summary)
left_df = left_df.astype(str)
right_df = right_df.astype(str)
df = '(' + left_df + ' ' + self.binary_op + ' ' + right_df + ')'
return df
class AggregateScore(object):
"""A special-purpose tally score used to encapsulate an aggregate of a
subset or all of tally's scores for tally aggregation.
Parameters
----------
scores : Iterable of str or CrossScore
The scores included in the aggregation
aggregate_op : str
The tally aggregation operator (e.g., 'sum', 'avg', etc.) used
to aggregate across a tally's scores with this AggregateScore
Attributes
----------
scores : Iterable of str or CrossScore
The scores included in the aggregation
aggregate_op : str
The tally aggregation operator (e.g., 'sum', 'avg', etc.) used
to aggregate across a tally's scores with this AggregateScore
"""
def __init__(self, scores=None, aggregate_op=None):
self._scores = None
self._aggregate_op = None
if scores is not None:
self.scores = scores
if aggregate_op is not None:
self.aggregate_op = aggregate_op
def __hash__(self):
return hash(repr(self))
def __eq__(self, other):
return str(other) == str(self)
def __ne__(self, other):
return not self == other
def __repr__(self):
string = ', '.join(map(str, self.scores))
string = '{0}({1})'.format(self.aggregate_op, string)
return string
@property
def scores(self):
return self._scores
@property
def aggregate_op(self):
return self._aggregate_op
@property
def name(self):
# Append each score in the aggregate to the string
string = '(' + ', '.join(self.scores) + ')'
return string
@scores.setter
def scores(self, scores):
cv.check_iterable_type('scores', scores, basestring)
self._scores = scores
@aggregate_op.setter
def aggregate_op(self, aggregate_op):
cv.check_type('aggregate_op', aggregate_op, (basestring, CrossScore))
cv.check_value('aggregate_op', aggregate_op, _TALLY_AGGREGATE_OPS)
self._aggregate_op = aggregate_op
class AggregateNuclide(object):
"""A special-purpose tally nuclide used to encapsulate an aggregate of a
subset or all of tally's nuclides for tally aggregation.
Parameters
----------
nuclides : Iterable of str or Nuclide or CrossNuclide
The nuclides included in the aggregation
aggregate_op : str
The tally aggregation operator (e.g., 'sum', 'avg', etc.) used
to aggregate across a tally's nuclides with this AggregateNuclide
Attributes
----------
nuclides : Iterable of str or Nuclide or CrossNuclide
The nuclides included in the aggregation
aggregate_op : str
The tally aggregation operator (e.g., 'sum', 'avg', etc.) used
to aggregate across a tally's nuclides with this AggregateNuclide
"""
def __init__(self, nuclides=None, aggregate_op=None):
self._nuclides = None
self._aggregate_op = None
if nuclides is not None:
self.nuclides = nuclides
if aggregate_op is not None:
self.aggregate_op = aggregate_op
def __hash__(self):
return hash(repr(self))
def __eq__(self, other):
return str(other) == str(self)
def __ne__(self, other):
return not self == other
def __repr__(self):
# Append each nuclide in the aggregate to the string
string = '{0}('.format(self.aggregate_op)
names = [nuclide.name if isinstance(nuclide, Nuclide) else str(nuclide)
for nuclide in self.nuclides]
string += ', '.join(map(str, names)) + ')'
return string
@property
def nuclides(self):
return self._nuclides
@property
def aggregate_op(self):
return self._aggregate_op
@property
def name(self):
# Append each nuclide in the aggregate to the string
names = [nuclide.name if isinstance(nuclide, Nuclide) else str(nuclide)
for nuclide in self.nuclides]
string = '(' + ', '.join(map(str, names)) + ')'
return string
@nuclides.setter
def nuclides(self, nuclides):
cv.check_iterable_type('nuclides', nuclides,
(basestring, Nuclide, CrossNuclide))
self._nuclides = nuclides
@aggregate_op.setter
def aggregate_op(self, aggregate_op):
cv.check_type('aggregate_op', aggregate_op, basestring)
cv.check_value('aggregate_op', aggregate_op, _TALLY_AGGREGATE_OPS)
self._aggregate_op = aggregate_op
class AggregateFilter(object):
"""A special-purpose tally filter used to encapsulate an aggregate of a
subset or all of a tally filter's bins for tally aggregation.
Parameters
----------
aggregate_filter : Filter or CrossFilter
The filter included in the aggregation
bins : Iterable of tuple
The filter bins included in the aggregation
aggregate_op : str
The tally aggregation operator (e.g., 'sum', 'avg', etc.) used
to aggregate across a tally filter's bins with this AggregateFilter
Attributes
----------
type : str
The type of the aggregatefilter (e.g., 'sum(energy)', 'sum(cell)')
aggregate_filter : filter
The filter included in the aggregation
aggregate_op : str
The tally aggregation operator (e.g., 'sum', 'avg', etc.) used
to aggregate across a tally filter's bins with this AggregateFilter
bins : Iterable of tuple
The filter bins included in the aggregation
num_bins : Integral
The number of filter bins (always 1 if aggregate_filter is defined)
stride : Integral
The number of filter, nuclide and score bins within each of this
aggregatefilter's bins.
"""
def __init__(self, aggregate_filter=None, bins=None, aggregate_op=None):
self._type = '{0}({1})'.format(aggregate_op, aggregate_filter.type)
self._bins = None
self._stride = None
self._aggregate_filter = None
self._aggregate_op = None
if aggregate_filter is not None:
self.aggregate_filter = aggregate_filter
if bins is not None:
self.bins = bins
if aggregate_op is not None:
self.aggregate_op = aggregate_op
def __hash__(self):
return hash(repr(self))
def __eq__(self, other):
return str(other) == str(self)
def __ne__(self, other):
return not self == other
def __gt__(self, other):
if self.type != other.type:
if self.aggregate_filter.type in _FILTER_TYPES and \
other.aggregate_filter.type in _FILTER_TYPES:
delta = _FILTER_TYPES.index(self.aggregate_filter.type) - \
_FILTER_TYPES.index(other.aggregate_filter.type)
return delta > 0
else:
return False
else:
return False
def __lt__(self, other):
return not self > other
def __repr__(self):
string = 'AggregateFilter\n'
string += '{0: <16}{1}{2}\n'.format('\tType', '=\t', self.type)
string += '{0: <16}{1}{2}\n'.format('\tBins', '=\t', self.bins)
return string
@property
def aggregate_filter(self):
return self._aggregate_filter
@property
def aggregate_op(self):
return self._aggregate_op
@property
def type(self):
return self._type
@property
def bins(self):
return self._bins
@property
def num_bins(self):
return len(self.bins) if self.aggregate_filter else 0
@property
def stride(self):
return self._stride
@type.setter
def type(self, filter_type):
if filter_type not in _FILTER_TYPES:
msg = 'Unable to set AggregateFilter type to "{0}" since it ' \
'is not one of the supported types'.format(filter_type)
raise ValueError(msg)
self._type = filter_type
@aggregate_filter.setter
def aggregate_filter(self, aggregate_filter):
cv.check_type('aggregate_filter', aggregate_filter, (Filter, CrossFilter))
self._aggregate_filter = aggregate_filter
@bins.setter
def bins(self, bins):
cv.check_iterable_type('bins', bins, Iterable)
self._bins = list(map(tuple, bins))
@aggregate_op.setter
def aggregate_op(self, aggregate_op):
cv.check_type('aggregate_op', aggregate_op, basestring)
cv.check_value('aggregate_op', aggregate_op, _TALLY_AGGREGATE_OPS)
self._aggregate_op = aggregate_op
@stride.setter
def stride(self, stride):
self._stride = stride
def get_bin_index(self, filter_bin):
"""Returns the index in the AggregateFilter for some bin.
Parameters
----------
filter_bin : Integral or tuple of Real
A tuple of value(s) corresponding to the bin of interest in
the aggregated filter. The bin is the integer ID for 'material',
'surface', 'cell', 'cellborn', and 'universe' Filters. The bin
is the integer cell instance ID for 'distribcell' Filters. The
bin is a 2-tuple of floats for 'energy' and 'energyout' filters
corresponding to the energy boundaries of the bin of interest.
The bin is a (x,y,z) 3-tuple for 'mesh' filters corresponding to
the mesh cell of interest.
Returns
-------
filter_index : Integral
The index in the Tally data array for this filter bin. For an
AggregateTally the filter bin index is always unity.
Raises
------
ValueError
When the filter_bin is not part of the aggregated filter's bins
"""
if filter_bin not in self.bins:
msg = 'Unable to get the bin index for AggregateFilter since ' \
'"{0}" is not one of the bins'.format(filter_bin)
raise ValueError(msg)
else:
return self.bins.index(filter_bin)
def get_pandas_dataframe(self, data_size, summary=None):
"""Builds a Pandas DataFrame for the AggregateFilter's bins.
This method constructs a Pandas DataFrame object for the AggregateFilter
with columns annotated by filter bin information. This is a helper
method for the Tally.get_pandas_dataframe(...) method.
Parameters
----------
data_size : Integral
The total number of bins in the tally corresponding to this filter
summary : None or Summary
An optional Summary object to be used to construct columns for
distribcell tally filters (default is None). NOTE: This parameter
is not used by the AggregateFilter and simply mirrors the method
signature for the CrossFilter.
Returns
-------
pandas.DataFrame
A Pandas DataFrame with columns of strings that characterize the
aggregatefilter's bins. Each entry in the DataFrame will include
one or more aggregation operations used to construct the
aggregatefilter's bins. The number of rows in the DataFrame is the
same as the total number of bins in the corresponding tally, with
the filter bins appropriately tiled to map to the corresponding
tally bins.
See also
--------
Tally.get_pandas_dataframe(), Filter.get_pandas_dataframe(),
CrossFilter.get_pandas_dataframe()
"""
import pandas as pd
# Create NumPy array of the bin tuples for repeating / tiling
filter_bins = np.empty(self.num_bins, dtype=tuple)
for i, bin in enumerate(self.bins):
filter_bins[i] = bin
# Repeat and tile bins as needed for DataFrame
filter_bins = np.repeat(filter_bins, self.stride)
tile_factor = data_size / len(filter_bins)
filter_bins = np.tile(filter_bins, tile_factor)
# Create DataFrame with aggregated bins
df = pd.DataFrame({self.type: filter_bins})
return df
def can_merge(self, other):
"""Determine if AggregateFilter can be merged with another.
Parameters
----------
other : AggregateFilter
Filter to compare with
Returns
-------
bool
Whether the filter can be merged
"""
if not isinstance(other, AggregateFilter):
return False
# Filters must be of the same type
elif self.type != other.type:
return False
# None of the bins in this filter should match in the other filter
for bin in self.bins:
if bin in other.bins:
return False
# If all conditional checks passed then filters are mergeable
return True
def merge(self, other):
"""Merge this aggregatefilter with another.
Parameters
----------
other : AggregateFilter
Filter to merge with
Returns
-------
merged_filter : AggregateFilter
Filter resulting from the merge
"""
if not self.can_merge(other):
msg = 'Unable to merge "{0}" with "{1}" ' \
'filters'.format(self.type, other.type)
raise ValueError(msg)
# Create deep copy of filter to return as merged filter
merged_filter = copy.deepcopy(self)
# Merge unique filter bins
merged_bins = self.bins + other.bins
# Sort energy bin edges
if 'energy' in self.type:
merged_bins = sorted(merged_bins)
# Assign merged bins to merged filter
merged_filter.bins = list(merged_bins)
return merged_filter

511
openmc/cell.py Normal file
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@ -0,0 +1,511 @@
from collections import OrderedDict, Iterable
from math import cos, sin, pi
from numbers import Real, Integral
from xml.etree import ElementTree as ET
import sys
import warnings
import numpy as np
import openmc
import openmc.checkvalue as cv
from openmc.surface import Halfspace
from openmc.region import Region, Intersection, Complement
if sys.version_info[0] >= 3:
basestring = str
# A static variable for auto-generated Cell IDs
AUTO_CELL_ID = 10000
def reset_auto_cell_id():
"""Reset counter for auto-generated cell IDs."""
global AUTO_CELL_ID
AUTO_CELL_ID = 10000
class Cell(object):
r"""A region of space defined as the intersection of half-space created by
quadric surfaces.
Parameters
----------
cell_id : int, optional
Unique identifier for the cell. If not specified, an identifier will
automatically be assigned.
name : str, optional
Name of the cell. If not specified, the name is the empty string.
fill : openmc.Material or openmc.Universe or openmc.Lattice or None or iterable of openmc.Material, optional
Indicates what the region of space is filled with
region : openmc.Region, optional
Region of space that is assigned to the cell.
Attributes
----------
id : int
Unique identifier for the cell
name : str
Name of the cell
fill : openmc.Material or openmc.Universe or openmc.Lattice or None or iterable of openmc.Material
Indicates what the region of space is filled with. If None, the cell is
treated as a void. An iterable of materials is used to fill repeated
instances of a cell with different materials.
fill_type : {'material', 'universe', 'lattice', 'distribmat', 'void'}
Indicates what the cell is filled with.
region : openmc.Region or None
Region of space that is assigned to the cell.
rotation : Iterable of float
If the cell is filled with a universe, this array specifies the angles
in degrees about the x, y, and z axes that the filled universe should be
rotated. The rotation applied is an intrinsic rotation with specified
Tait-Bryan angles. That is to say, if the angles are :math:`(\phi,
\theta, \psi)`, then the rotation matrix applied is :math:`R_z(\psi)
R_y(\theta) R_x(\phi)` or
.. math::
\left [ \begin{array}{ccc} \cos\theta \cos\psi & -\cos\theta \sin\psi
+ \sin\phi \sin\theta \cos\psi & \sin\phi \sin\psi + \cos\phi
\sin\theta \cos\psi \\ \cos\theta \sin\psi & \cos\phi \cos\psi +
\sin\phi \sin\theta \sin\psi & -\sin\phi \cos\psi + \cos\phi
\sin\theta \sin\psi \\ -\sin\theta & \sin\phi \cos\theta & \cos\phi
\cos\theta \end{array} \right ]
rotation_matrix : numpy.ndarray
The rotation matrix defined by the angles specified in the
:attr:`Cell.rotation` property.
temperature : float or iterable of float
Temperature of the cell in Kelvin. Multiple temperatures can be given
to give each distributed cell instance a unique temperature.
translation : Iterable of float
If the cell is filled with a universe, this array specifies a vector
that is used to translate (shift) the universe.
offsets : ndarray
Array of offsets used for distributed cell searches
distribcell_index : int
Index of this cell in distribcell arrays
"""
def __init__(self, cell_id=None, name='', fill=None, region=None):
# Initialize Cell class attributes
self.id = cell_id
self.name = name
self.fill = fill
self.region = region
self._rotation = None
self._rotation_matrix = None
self._temperature = None
self._translation = None
self._offsets = None
self._distribcell_index = None
def __contains__(self, point):
if self.region is None:
return True
else:
return point in self.region
def __eq__(self, other):
if not isinstance(other, Cell):
return False
elif self.id != other.id:
return False
elif self.name != other.name:
return False
elif self.fill != other.fill:
return False
elif self.region != other.region:
return False
elif self.rotation != other.rotation:
return False
elif self.temperature != other.temperature:
return False
elif self.translation != other.translation:
return False
else:
return True
def __ne__(self, other):
return not self == other
def __hash__(self):
return hash(repr(self))
def __repr__(self):
string = 'Cell\n'
string += '{: <16}=\t{}\n'.format('\tID', self.id)
string += '{: <16}=\t{}\n'.format('\tName', self.name)
if self.fill_type == 'material':
string += '{: <16}=\tMaterial {}\n'.format('\tFill', self.fill.id)
elif self.fill_type == 'void':
string += '{: <16}=\tNone\n'.format('\tFill')
elif self.fill_type == 'distribmat':
string += '{: <16}=\t{}\n'.format('\tFill', list(map(
lambda m: m if m is None else m.id, self.fill)))
else:
string += '{: <16}=\t{}\n'.format('\tFill', self.fill.id)
string += '{: <16}=\t{}\n'.format('\tRegion', self.region)
string += '{: <16}=\t{}\n'.format('\tRotation', self.rotation)
if self.fill_type == 'material':
string += '\t{0: <15}=\t{1}\n'.format('Temperature',
self.temperature)
string += '{: <16}=\t{}\n'.format('\tTranslation', self.translation)
string += '{: <16}=\t{}\n'.format('\tOffset', self.offsets)
string += '{: <16}=\t{}\n'.format('\tDistribcell index', self.distribcell_index)
return string
@property
def id(self):
return self._id
@property
def name(self):
return self._name
@property
def fill(self):
return self._fill
@property
def fill_type(self):
if isinstance(self.fill, openmc.Material):
return 'material'
elif isinstance(self.fill, openmc.Universe):
return 'universe'
elif isinstance(self.fill, openmc.Lattice):
return 'lattice'
elif isinstance(self.fill, Iterable):
return 'distribmat'
else:
return 'void'
@property
def region(self):
return self._region
@property
def rotation(self):
return self._rotation
@property
def rotation_matrix(self):
return self._rotation_matrix
@property
def temperature(self):
return self._temperature
@property
def translation(self):
return self._translation
@property
def offsets(self):
return self._offsets
@property
def distribcell_index(self):
return self._distribcell_index
@id.setter
def id(self, cell_id):
if cell_id is None:
global AUTO_CELL_ID
self._id = AUTO_CELL_ID
AUTO_CELL_ID += 1
else:
cv.check_type('cell ID', cell_id, Integral)
cv.check_greater_than('cell ID', cell_id, 0, equality=True)
self._id = cell_id
@name.setter
def name(self, name):
if name is not None:
cv.check_type('cell name', name, basestring)
self._name = name
else:
self._name = ''
@fill.setter
def fill(self, fill):
if fill is not None:
if isinstance(fill, basestring):
if fill.strip().lower() != 'void':
msg = 'Unable to set Cell ID="{0}" to use a non-Material ' \
'or Universe fill "{1}"'.format(self._id, fill)
raise ValueError(msg)
fill = None
elif isinstance(fill, Iterable):
for i, f in enumerate(fill):
if f is not None:
cv.check_type('cell.fill[i]', f, openmc.Material)
elif not isinstance(fill, (openmc.Material, openmc.Lattice,
openmc.Universe)):
msg = 'Unable to set Cell ID="{0}" to use a non-Material or ' \
'Universe fill "{1}"'.format(self._id, fill)
raise ValueError(msg)
self._fill = fill
@rotation.setter
def rotation(self, rotation):
if not isinstance(self.fill, openmc.Universe):
raise RuntimeError('Cell rotation can only be applied if the cell '
'is filled with a Universe')
cv.check_type('cell rotation', rotation, Iterable, Real)
cv.check_length('cell rotation', rotation, 3)
self._rotation = np.asarray(rotation)
# Save rotation matrix
phi, theta, psi = self.rotation*(-pi/180.)
c3, s3 = cos(phi), sin(phi)
c2, s2 = cos(theta), sin(theta)
c1, s1 = cos(psi), sin(psi)
self._rotation_matrix = np.array([
[c1*c2, c1*s2*s3 - c3*s1, s1*s3 + c1*c3*s2],
[c2*s1, c1*c3 + s1*s2*s3, c3*s1*s2 - c1*s3],
[-s2, c2*s3, c2*c3]])
@translation.setter
def translation(self, translation):
cv.check_type('cell translation', translation, Iterable, Real)
cv.check_length('cell translation', translation, 3)
self._translation = np.asarray(translation)
@temperature.setter
def temperature(self, temperature):
cv.check_type('cell temperature', temperature, (Iterable, Real))
if isinstance(temperature, Iterable):
cv.check_type('cell temperature', temperature, Iterable, Real)
for T in temperature:
cv.check_greater_than('cell temperature', T, 0.0, True)
else:
cv.check_greater_than('cell temperature', temperature, 0.0, True)
self._temperature = temperature
@offsets.setter
def offsets(self, offsets):
cv.check_type('cell offsets', offsets, Iterable)
self._offsets = offsets
@region.setter
def region(self, region):
if region is not None:
cv.check_type('cell region', region, Region)
self._region = region
@distribcell_index.setter
def distribcell_index(self, ind):
cv.check_type('distribcell index', ind, Integral)
self._distribcell_index = ind
def add_surface(self, surface, halfspace):
"""Add a half-space to the list of half-spaces whose intersection defines the
cell.
.. deprecated:: 0.7.1
Use the :attr:`Cell.region` property to directly specify a Region
expression.
Parameters
----------
surface : openmc.Surface
Quadric surface dividing space
halfspace : {-1, 1}
Indicate whether the negative or positive half-space is to be used
"""
warnings.warn("Cell.add_surface(...) has been deprecated and may be "
"removed in a future version. The region for a Cell "
"should be defined using the region property directly.",
DeprecationWarning)
if not isinstance(surface, openmc.Surface):
msg = 'Unable to add Surface "{0}" to Cell ID="{1}" since it is ' \
'not a Surface object'.format(surface, self._id)
raise ValueError(msg)
if halfspace not in [-1, +1]:
msg = 'Unable to add Surface "{0}" to Cell ID="{1}" with halfspace ' \
'"{2}" since it is not +/-1'.format(surface, self._id, halfspace)
raise ValueError(msg)
# If no region has been assigned, simply use the half-space. Otherwise,
# take the intersection of the current region and the half-space
# specified
region = +surface if halfspace == 1 else -surface
if self.region is None:
self.region = region
else:
if isinstance(self.region, Intersection):
self.region.nodes.append(region)
else:
self.region = Intersection(self.region, region)
def get_cell_instance(self, path, distribcell_index):
# If the Cell is filled by a Material
if self.fill_type in ('material', 'distribmat', 'void'):
offset = 0
# If the Cell is filled by a Universe
elif self.fill_type == 'universe':
offset = self.offsets[distribcell_index-1]
offset += self.fill.get_cell_instance(path, distribcell_index)
# If the Cell is filled by a Lattice
else:
offset = self.fill.get_cell_instance(path, distribcell_index)
return offset
def get_all_nuclides(self):
"""Return all nuclides contained in the cell
Returns
-------
nuclides : dict
Dictionary whose keys are nuclide names and values are 2-tuples of
(nuclide, density)
"""
nuclides = OrderedDict()
if self.fill_type != 'void':
nuclides.update(self.fill.get_all_nuclides())
return nuclides
def get_all_cells(self):
"""Return all cells that are contained within this one if it is filled with a
universe or lattice
Returns
-------
cells : dict
Dictionary whose keys are cell IDs and values are :class:`Cell`
instances
"""
cells = OrderedDict()
if self.fill_type in ('universe', 'lattice'):
cells.update(self.fill.get_all_cells())
return cells
def get_all_materials(self):
"""Return all materials that are contained within the cell
Returns
-------
materials : dict
Dictionary whose keys are material IDs and values are
:class:`Material` instances
"""
materials = OrderedDict()
if self.fill_type == 'material':
materials[self.fill.id] = self.fill
# Append all Cells in each Cell in the Universe to the dictionary
cells = self.get_all_cells()
for cell in cells.values():
materials.update(cell.get_all_materials())
return materials
def get_all_universes(self):
"""Return all universes that are contained within this one if any of
its cells are filled with a universe or lattice.
Returns
-------
universes : dict
Dictionary whose keys are universe IDs and values are
:class:`Universe` instances
"""
universes = OrderedDict()
if self.fill_type == 'universe':
universes[self.fill.id] = self.fill
universes.update(self.fill.get_all_universes())
elif self.fill_type == 'lattice':
universes.update(self.fill.get_all_universes())
return universes
def create_xml_subelement(self, xml_element):
element = ET.Element("cell")
element.set("id", str(self.id))
if len(self._name) > 0:
element.set("name", str(self.name))
if self.fill_type == 'void':
element.set("material", "void")
elif self.fill_type == 'material':
element.set("material", str(self.fill.id))
elif self.fill_type == 'distribmat':
element.set("material", ' '.join(['void' if m is None else str(m.id)
for m in self.fill]))
elif self.fill_type in ('universe', 'lattice'):
element.set("fill", str(self.fill.id))
self.fill.create_xml_subelement(xml_element)
if self.region is not None:
# Set the region attribute with the region specification
element.set("region", str(self.region))
# Only surfaces that appear in a region are added to the geometry
# file, so the appropriate check is performed here. First we create
# a function which is called recursively to navigate through the CSG
# tree. When it reaches a leaf (a Halfspace), it creates a <surface>
# element for the corresponding surface if none has been created
# thus far.
def create_surface_elements(node, element):
if isinstance(node, Halfspace):
path = './surface[@id=\'{0}\']'.format(node.surface.id)
if xml_element.find(path) is None:
surface_subelement = node.surface.create_xml_subelement()
xml_element.append(surface_subelement)
elif isinstance(node, Complement):
create_surface_elements(node.node, element)
else:
for subnode in node.nodes:
create_surface_elements(subnode, element)
# Call the recursive function from the top node
create_surface_elements(self.region, xml_element)
if self.temperature is not None:
if isinstance(self.temperature, Iterable):
element.set("temperature", ' '.join(
str(t) for t in self.temperature))
else:
element.set("temperature", str(self.temperature))
if self.translation is not None:
element.set("translation", ' '.join(map(str, self.translation)))
if self.rotation is not None:
element.set("rotation", ' '.join(map(str, self.rotation)))
return element

143
openmc/checkvalue.py
View file

@ -1,35 +1,8 @@
import copy
from collections import Iterable
from numbers import Integral, Real
import numpy as np
def _isinstance(value, expected_type):
"""A Numpy-aware replacement for isinstance
This function will be obsolete when Numpy v. >= 1.9 is established.
"""
# Declare numpy numeric types.
np_ints = (np.int_, np.intc, np.intp, np.int8, np.int16, np.int32, np.int64,
np.uint8, np.uint16, np.uint32, np.uint64)
np_floats = (np.float_, np.float16, np.float32, np.float64)
# Include numpy integers, if necessary.
if type(expected_type) is tuple:
if Integral in expected_type:
expected_type = expected_type + np_ints
elif expected_type is Integral:
expected_type = (Integral, ) + np_ints
# Include numpy floats, if necessary.
if type(expected_type) is tuple:
if Real in expected_type:
expected_type = expected_type + np_floats
elif expected_type is Real:
expected_type = (Real, ) + np_floats
# Now, make the instance check.
return isinstance(value, expected_type)
def check_type(name, value, expected_type, expected_iter_type=None):
"""Ensure that an object is of an expected type. Optionally, if the object is
@ -41,26 +14,45 @@ def check_type(name, value, expected_type, expected_iter_type=None):
Description of value being checked
value : object
Object to check type of
expected_type : type
expected_type : type or Iterable of type
type to check object against
expected_iter_type : type or None, optional
expected_iter_type : type or Iterable of type or None, optional
Expected type of each element in value, assuming it is iterable. If
None, no check will be performed.
"""
if not _isinstance(value, expected_type):
msg = 'Unable to set "{0}" to "{1}" which is not of type "{2}"'.format(
name, value, expected_type.__name__)
raise ValueError(msg)
if not isinstance(value, expected_type):
if isinstance(expected_type, Iterable):
msg = 'Unable to set "{0}" to "{1}" which is not one of the ' \
'following types: "{2}"'.format(name, value, ', '.join(
[t.__name__ for t in expected_type]))
else:
msg = 'Unable to set "{0}" to "{1}" which is not of type "{2}"'.format(
name, value, expected_type.__name__)
raise TypeError(msg)
if expected_iter_type:
for item in value:
if not _isinstance(item, expected_iter_type):
if isinstance(value, np.ndarray):
if not issubclass(value.dtype.type, expected_iter_type):
msg = 'Unable to set "{0}" to "{1}" since each item must be ' \
'of type "{2}"'.format(name, value,
expected_iter_type.__name__)
raise ValueError(msg)
expected_iter_type.__name__)
else:
return
for item in value:
if not isinstance(item, expected_iter_type):
if isinstance(expected_iter_type, Iterable):
msg = 'Unable to set "{0}" to "{1}" since each item must be ' \
'one of the following types: "{2}"'.format(
name, value, ', '.join([t.__name__ for t in
expected_iter_type]))
else:
msg = 'Unable to set "{0}" to "{1}" since each item must be ' \
'of type "{2}"'.format(name, value,
expected_iter_type.__name__)
raise TypeError(msg)
def check_iterable_type(name, value, expected_type, min_depth=1, max_depth=1):
@ -106,12 +98,12 @@ def check_iterable_type(name, value, expected_type, min_depth=1, max_depth=1):
# If this item is of the expected type, then we've reached the bottom
# level of this branch.
if _isinstance(current_item, expected_type):
if isinstance(current_item, expected_type):
# Is this deep enough?
if len(tree) < min_depth:
msg = 'Error setting "{0}": The item at {1} does not meet the '\
'minimum depth of {2}'.format(name, ind_str, min_depth)
raise ValueError(msg)
raise TypeError(msg)
# This item is okay. Move on to the next item.
index[-1] += 1
@ -127,9 +119,9 @@ def check_iterable_type(name, value, expected_type, min_depth=1, max_depth=1):
# But first, have we exceeded the max depth?
if len(tree) > max_depth:
msg = 'Error setting {0}: Found an iterable at {1}, items '\
'in that iterable excceed the maximum depth of {2}' \
'in that iterable exceed the maximum depth of {2}' \
.format(name, ind_str, max_depth)
raise ValueError(msg)
raise TypeError(msg)
else:
# This item is completely unexpected.
@ -137,7 +129,7 @@ def check_iterable_type(name, value, expected_type, min_depth=1, max_depth=1):
"item at {2} is of type '{3}'"\
.format(name, expected_type.__name__, ind_str,
type(current_item).__name__)
raise ValueError(msg)
raise TypeError(msg)
def check_length(name, value, length_min, length_max=None):
@ -169,7 +161,7 @@ def check_length(name, value, length_min, length_max=None):
else:
msg = 'Unable to set "{0}" to "{1}" since it must have length ' \
'between "{2}" and "{3}"'.format(name, value, length_min,
length_max)
length_max)
raise ValueError(msg)
@ -245,3 +237,66 @@ def check_greater_than(name, value, minimum, equality=False):
msg = 'Unable to set "{0}" to "{1}" since it is less than ' \
'or equal to "{2}"'.format(name, value, minimum)
raise ValueError(msg)
class CheckedList(list):
"""A list for which each element is type-checked as it's added
Parameters
----------
expected_type : type or Iterable of type
Type(s) which each element should be
name : str
Name of data being checked
items : Iterable, optional
Items to initialize the list with
"""
def __init__(self, expected_type, name, items=[]):
super(CheckedList, self).__init__()
self.expected_type = expected_type
self.name = name
for item in items:
self.append(item)
def __add__(self, other):
new_instance = copy.copy(self)
new_instance += other
return new_instance
def __radd__(self, other):
return self + other
def __iadd__(self, other):
check_type('CheckedList add operand', other, Iterable,
self.expected_type)
for item in other:
self.append(item)
return self
def append(self, item):
"""Append item to list
Parameters
----------
item : object
Item to append
"""
check_type(self.name, item, self.expected_type)
super(CheckedList, self).append(item)
def insert(self, index, item):
"""Insert item before index
Parameters
----------
index : int
Index in list
item : object
Item to insert
"""
check_type(self.name, item, self.expected_type)
super(CheckedList, self).insert(index, item)

12
openmc/cmfd.py
View file

@ -15,9 +15,7 @@ from numbers import Real, Integral
from xml.etree import ElementTree as ET
import sys
import numpy as np
from openmc.clean_xml import *
from openmc.clean_xml import clean_xml_indentation
from openmc.checkvalue import (check_type, check_length, check_value,
check_greater_than, check_less_than)
@ -69,7 +67,7 @@ class CMFDMesh(object):
to any tallies far away from fission source neutron regions. A ``2``
must be used to identify any fission source region.
"""
"""
def __init__(self):
self._lower_left = None
@ -187,8 +185,8 @@ class CMFDMesh(object):
return element
class CMFDFile(object):
"""Parameters that control the use of coarse-mesh finite difference acceleration
class CMFD(object):
r"""Parameters that control the use of coarse-mesh finite difference acceleration
in OpenMC. This corresponds directly to the cmfd.xml input file.
Attributes
@ -219,7 +217,7 @@ class CMFDFile(object):
inner tolerance for Gauss-Seidel iterations when performing CMFD.
ktol : float
Tolerance on the eigenvalue when performing CMFD power iteration
cmfd_mesh : CMFDMesh
cmfd_mesh : openmc.CMFDMesh
Structured mesh to be used for acceleration
norm : float
Normalization factor applied to the CMFD fission source distribution

465
openmc/cross.py
View file

@ -1,465 +0,0 @@
import sys
from openmc import Filter, Nuclide
from openmc.filter import _FILTER_TYPES
import openmc.checkvalue as cv
if sys.version_info[0] >= 3:
basestring = str
# Acceptable tally arithmetic binary operations
_TALLY_ARITHMETIC_OPS = ['+', '-', '*', '/', '^']
class CrossScore(object):
"""A special-purpose tally score used to encapsulate all combinations of two
tally's scores as an outer product for tally arithmetic.
Parameters
----------
left_score : str or CrossScore
The left score in the outer product
right_score : str or CrossScore
The right score in the outer product
binary_op : str
The tally arithmetic binary operator (e.g., '+', '-', etc.) used to
combine two tally's scores with this CrossNuclide
Attributes
----------
left_score : str or CrossScore
The left score in the outer product
right_score : str or CrossScore
The right score in the outer product
binary_op : str
The tally arithmetic binary operator (e.g., '+', '-', etc.) used to
combine two tally's scores with this CrossNuclide
"""
def __init__(self, left_score=None, right_score=None, binary_op=None):
self._left_score = None
self._right_score = None
self._binary_op = None
if left_score is not None:
self.left_score = left_score
if right_score is not None:
self.right_score = right_score
if binary_op is not None:
self.binary_op = binary_op
def __hash__(self):
return hash(repr(self))
def __eq__(self, other):
return str(other) == str(self)
def __ne__(self, other):
return not self == other
def __deepcopy__(self, memo):
existing = memo.get(id(self))
# If this is the first time we have tried to copy this object, create a copy
if existing is None:
clone = type(self).__new__(type(self))
clone._left_score = self.left_score
clone._right_score = self.right_score
clone._binary_op = self.binary_op
memo[id(self)] = clone
return clone
# If this object has been copied before, return the first copy made
else:
return existing
def __repr__(self):
string = '({0} {1} {2})'.format(self.left_score,
self.binary_op, self.right_score)
return string
@property
def left_score(self):
return self._left_score
@property
def right_score(self):
return self._right_score
@property
def binary_op(self):
return self._binary_op
@left_score.setter
def left_score(self, left_score):
cv.check_type('left_score', left_score, (basestring, CrossScore))
self._left_score = left_score
@right_score.setter
def right_score(self, right_score):
cv.check_type('right_score', right_score, (basestring, CrossScore))
self._right_score = right_score
@binary_op.setter
def binary_op(self, binary_op):
cv.check_type('binary_op', binary_op, (basestring, CrossScore))
cv.check_value('binary_op', binary_op, _TALLY_ARITHMETIC_OPS)
self._binary_op = binary_op
class CrossNuclide(object):
"""A special-purpose nuclide used to encapsulate all combinations of two
tally's nuclides as an outer product for tally arithmetic.
Parameters
----------
left_nuclide : Nuclide or CrossNuclide
The left nuclide in the outer product
right_nuclide : Nuclide or CrossNuclide
The right nuclide in the outer product
binary_op : str
The tally arithmetic binary operator (e.g., '+', '-', etc.) used to
combine two tally's nuclides with this CrossNuclide
Attributes
----------
left_nuclide : Nuclide or CrossNuclide
The left nuclide in the outer product
right_nuclide : Nuclide or CrossNuclide
The right nuclide in the outer product
binary_op : str
The tally arithmetic binary operator (e.g., '+', '-', etc.) used to
combine two tally's nuclides with this CrossNuclide
"""
def __init__(self, left_nuclide=None, right_nuclide=None, binary_op=None):
self._left_nuclide = None
self._right_nuclide = None
self._binary_op = None
if left_nuclide is not None:
self.left_nuclide = left_nuclide
if right_nuclide is not None:
self.right_nuclide = right_nuclide
if binary_op is not None:
self.binary_op = binary_op
def __hash__(self):
return hash(repr(self))
def __eq__(self, other):
return str(other) == str(self)
def __ne__(self, other):
return not self == other
def __deepcopy__(self, memo):
existing = memo.get(id(self))
# If this is the first time we have tried to copy this object, create a copy
if existing is None:
clone = type(self).__new__(type(self))
clone._left_nuclide = self.left_nuclide
clone._right_nuclide = self.right_nuclide
clone._binary_op = self.binary_op
memo[id(self)] = clone
return clone
# If this object has been copied before, return the first copy made
else:
return existing
def __repr__(self):
string = ''
# If the Summary was linked, the left nuclide is a Nuclide object
if isinstance(self.left_nuclide, Nuclide):
string += '(' + self.left_nuclide.name
# If the Summary was not linked, the left nuclide is the ZAID
else:
string += '(' + str(self.left_nuclide)
string += ' ' + self.binary_op + ' '
# If the Summary was linked, the right nuclide is a Nuclide object
if isinstance(self.right_nuclide, Nuclide):
string += self.right_nuclide.name + ')'
# If the Summary was not linked, the right nuclide is the ZAID
else:
string += str(self.right_nuclide) + ')'
return string
@property
def left_nuclide(self):
return self._left_nuclide
@property
def right_nuclide(self):
return self._right_nuclide
@property
def binary_op(self):
return self._binary_op
@left_nuclide.setter
def left_nuclide(self, left_nuclide):
cv.check_type('left_nuclide', left_nuclide, (Nuclide, CrossNuclide))
self._left_nuclide = left_nuclide
@right_nuclide.setter
def right_nuclide(self, right_nuclide):
cv.check_type('right_nuclide', right_nuclide, (Nuclide, CrossNuclide))
self._right_nuclide = right_nuclide
@binary_op.setter
def binary_op(self, binary_op):
cv.check_type('binary_op', binary_op, basestring)
cv.check_value('binary_op', binary_op, _TALLY_ARITHMETIC_OPS)
self._binary_op = binary_op
class CrossFilter(object):
"""A special-purpose filter used to encapsulate all combinations of two
tally's filter bins as an outer product for tally arithmetic.
Parameters
----------
left_filter : Filter or CrossFilter
The left filter in the outer product
right_filter : Filter or CrossFilter
The right filter in the outer product
binary_op : str
The tally arithmetic binary operator (e.g., '+', '-', etc.) used to
combine two tally's filter bins with this CrossFilter
Attributes
----------
left_filter : Filter or CrossFilter
The left filter in the outer product
right_filter : Filter or CrossFilter
The right filter in the outer product
binary_op : str
The tally arithmetic binary operator (e.g., '+', '-', etc.) used to
combine two tally's filter bins with this CrossFilter
"""
def __init__(self, left_filter=None, right_filter=None, binary_op=None):
left_type = left_filter.type
right_type = right_filter.type
self._type = '({0} {1} {2})'.format(left_type, binary_op, right_type)
self._bins = {}
self._stride = None
self._left_filter = None
self._right_filter = None
self._binary_op = None
if left_filter is not None:
self.left_filter = left_filter
self._bins['left'] = left_filter.bins
if right_filter is not None:
self.right_filter = right_filter
self._bins['right'] = right_filter.bins
if binary_op is not None:
self.binary_op = binary_op
def __hash__(self):
return hash((self.left_filter, self.right_filter))
def __eq__(self, other):
return str(other) == str(self)
def __ne__(self, other):
return not self == other
def __repr__(self):
string = 'CrossFilter\n'
filter_type = '({0} {1} {2})'.format(self.left_filter.type,
self.binary_op,
self.right_filter.type)
filter_bins = '({0} {1} {2})'.format(self.left_filter.bins,
self.binary_op,
self.right_filter.bins)
string += '{0: <16}{1}{2}\n'.format('\tType', '=\t', filter_type)
string += '{0: <16}{1}{2}\n'.format('\tBins', '=\t', filter_bins)
return string
def __deepcopy__(self, memo):
existing = memo.get(id(self))
# If this is the first time we have tried to copy this object, create a copy
if existing is None:
clone = type(self).__new__(type(self))
clone._left_filter = self.left_filter
clone._right_filter = self.right_filter
clone._binary_op = self.binary_op
clone._type = self.type
clone._bins = self._bins
clone._num_bins = self.num_bins
clone._stride = self.stride
memo[id(self)] = clone
return clone
# If this object has been copied before, return the first copy made
else:
return existing
@property
def left_filter(self):
return self._left_filter
@property
def right_filter(self):
return self._right_filter
@property
def binary_op(self):
return self._binary_op
@property
def type(self):
return self._type
@property
def bins(self):
return self._bins['left'], self._bins['right']
@property
def num_bins(self):
if self.left_filter is not None and self.right_filter is not None:
return self.left_filter.num_bins * self.right_filter.num_bins
else:
return 0
@property
def stride(self):
return self._stride
@type.setter
def type(self, filter_type):
if filter_type not in _FILTER_TYPES.values():
msg = 'Unable to set Filter type to "{0}" since it is not one ' \
'of the supported types'.format(filter_type)
raise ValueError(msg)
self._type = filter_type
@left_filter.setter
def left_filter(self, left_filter):
cv.check_type('left_filter', left_filter, (Filter, CrossFilter))
self._left_filter = left_filter
self._bins['left'] = left_filter.bins
@right_filter.setter
def right_filter(self, right_filter):
cv.check_type('right_filter', right_filter, (Filter, CrossFilter))
self._right_filter = right_filter
self._bins['right'] = right_filter.bins
@binary_op.setter
def binary_op(self, binary_op):
cv.check_type('binary_op', binary_op, basestring)
cv.check_value('binary_op', binary_op, _TALLY_ARITHMETIC_OPS)
self._binary_op = binary_op
@stride.setter
def stride(self, stride):
self._stride = stride
def get_bin_index(self, filter_bin):
"""Returns the index in the CrossFilter for some bin.
Parameters
----------
filter_bin : 2-tuple
A 2-tuple where each value corresponds to the bin of interest
in the left and right filter, respectively. A bin is the integer
ID for 'material', 'surface', 'cell', 'cellborn', and 'universe'
Filters. The bin is an integer for the cell instance ID for
'distribcell' Filters. The bin is a 2-tuple of floats for 'energy'
and 'energyout' filters corresponding to the energy boundaries of
the bin of interest. The bin is a (x,y,z) 3-tuple for 'mesh'
filters corresponding to the mesh cell of interest.
Returns
-------
filter_index : Integral
The index in the Tally data array for this filter bin.
"""
left_index = self.left_filter.get_bin_index(filter_bin[0])
right_index = self.right_filter.get_bin_index(filter_bin[0])
filter_index = left_index * self.right_filter.num_bins + right_index
return filter_index
def get_pandas_dataframe(self, datasize, summary=None):
"""Builds a Pandas DataFrame for the CrossFilter's bins.
This method constructs a Pandas DataFrame object for the CrossFilter
with columns annotated by filter bin information. This is a helper
method for the Tally.get_pandas_dataframe(...) method. This method
recursively builds and concatenates Pandas DataFrames for the left
and right filters and crossfilters.
This capability has been tested for Pandas >=0.13.1. However, it is
recommended to use v0.16 or newer versions of Pandas since this method
uses Pandas' Multi-index functionality.
Parameters
----------
datasize : Integral
The total number of bins in the tally corresponding to this filter
summary : None or Summary
An optional Summary object to be used to construct columns for
distribcell tally filters (default is None). The geometric
information in the Summary object is embedded into a Multi-index
column with a geometric "path" to each distribcell instance.
NOTE: This option requires the OpenCG Python package.
Returns
-------
pandas.DataFrame
A Pandas DataFrame with columns of strings that characterize the
crossfilter's bins. Each entry in the DataFrame will include one
or more binary operations used to construct the crossfilter's bins.
The number of rows in the DataFrame is the same as the total number
of bins in the corresponding tally, with the filter bins
appropriately tiled to map to the corresponding tally bins.
See also
--------
Tally.get_pandas_dataframe(), Filter.get_pandas_dataframe()
"""
# If left and right filters are identical, do not combine bins
if self.left_filter == self.right_filter:
df = self.left_filter.get_pandas_dataframe(datasize, summary)
# If left and right filters are different, combine their bins
else:
left_df = self.left_filter.get_pandas_dataframe(datasize, summary)
right_df = self.right_filter.get_pandas_dataframe(datasize, summary)
left_df = left_df.astype(str)
right_df = right_df.astype(str)
df = '(' + left_df + ' ' + self.binary_op + ' ' + right_df + ')'
return df

1
openmc/data/__init__.py Normal file
View file

@ -0,0 +1 @@
from .data import *

101
openmc/data/data.py Normal file
View file

@ -0,0 +1,101 @@
# Isotopic abundances from M. Berglund and M. E. Wieser, "Isotopic compositions
# of the elements 2009 (IUPAC Technical Report)", Pure. Appl. Chem. 83 (2),
# pp. 397--410 (2011).
natural_abundance = {
'H-1': 0.999885, 'H-2': 0.000115, 'He-3': 1.34e-06,
'He-4': 0.99999866, 'Li-6': 0.0759, 'Li-7': 0.9241,
'Be-9': 1.0, 'B-10': 0.199, 'B-11': 0.801,
'C-12': 0.9893, 'C-13': 0.0107, 'N-14': 0.99636,
'N-15': 0.00364, 'O-16': 0.99757, 'O-17': 0.00038,
'O-18': 0.00205, 'F-19': 1.0, 'Ne-20': 0.9048,
'Ne-21': 0.0027, 'Ne-22': 0.0925, 'Na-23': 1.0,
'Mg-24': 0.7899, 'Mg-25': 0.1, 'Mg-26': 0.1101,
'Al-27': 1.0, 'Si-28': 0.92223, 'Si-29': 0.04685,
'Si-30': 0.03092, 'P-31': 1.0, 'S-32': 0.9499,
'S-33': 0.0075, 'S-34': 0.0425, 'S-36': 0.0001,
'Cl-35': 0.7576, 'Cl-37': 0.2424, 'Ar-36': 0.003336,
'Ar-38': 0.000629, 'Ar-40': 0.996035, 'K-39': 0.932581,
'K-40': 0.000117, 'K-41': 0.067302, 'Ca-40': 0.96941,
'Ca-42': 0.00647, 'Ca-43': 0.00135, 'Ca-44': 0.02086,
'Ca-46': 4e-05, 'Ca-48': 0.00187, 'Sc-45': 1.0,
'Ti-46': 0.0825, 'Ti-47': 0.0744, 'Ti-48': 0.7372,
'Ti-49': 0.0541, 'Ti-50': 0.0518, 'V-50': 0.0025,
'V-51': 0.9975, 'Cr-50': 0.04345, 'Cr-52': 0.83789,
'Cr-53': 0.09501, 'Cr-54': 0.02365, 'Mn-55': 1.0,
'Fe-54': 0.05845, 'Fe-56': 0.91754, 'Fe-57': 0.02119,
'Fe-58': 0.00282, 'Co-59': 1.0, 'Ni-58': 0.68077,
'Ni-60': 0.26223, 'Ni-61': 0.011399, 'Ni-62': 0.036346,
'Ni-64': 0.009255, 'Cu-63': 0.6915, 'Cu-65': 0.3085,
'Zn-64': 0.4917, 'Zn-66': 0.2773, 'Zn-67': 0.0404,
'Zn-68': 0.1845, 'Zn-70': 0.0061, 'Ga-69': 0.60108,
'Ga-71': 0.39892, 'Ge-70': 0.2057, 'Ge-72': 0.2745,
'Ge-73': 0.0775, 'Ge-74': 0.365, 'Ge-76': 0.0773,
'As-75': 1.0, 'Se-74': 0.0089, 'Se-76': 0.0937,
'Se-77': 0.0763, 'Se-78': 0.2377, 'Se-80': 0.4961,
'Se-82': 0.0873, 'Br-79': 0.5069, 'Br-81': 0.4931,
'Kr-78': 0.00355, 'Kr-80': 0.02286, 'Kr-82': 0.11593,
'Kr-83': 0.115, 'Kr-84': 0.56987, 'Kr-86': 0.17279,
'Rb-85': 0.7217, 'Rb-87': 0.2783, 'Sr-84': 0.0056,
'Sr-86': 0.0986, 'Sr-87': 0.07, 'Sr-88': 0.8258,
'Y-89': 1.0, 'Zr-90': 0.5145, 'Zr-91': 0.1122,
'Zr-92': 0.1715, 'Zr-94': 0.1738, 'Zr-96': 0.028,
'Nb-93': 1.0, 'Mo-92': 0.1453, 'Mo-94': 0.0915,
'Mo-95': 0.1584, 'Mo-96': 0.1667, 'Mo-97': 0.096,
'Mo-98': 0.2439, 'Mo-100': 0.0982, 'Ru-96': 0.0554,
'Ru-98': 0.0187, 'Ru-99': 0.1276, 'Ru-100': 0.126,
'Ru-101': 0.1706, 'Ru-102': 0.3155, 'Ru-104': 0.1862,
'Rh-103': 1.0, 'Pd-102': 0.0102, 'Pd-104': 0.1114,
'Pd-105': 0.2233, 'Pd-106': 0.2733, 'Pd-108': 0.2646,
'Pd-110': 0.1172, 'Ag-107': 0.51839, 'Ag-109': 0.48161,
'Cd-106': 0.0125, 'Cd-108': 0.0089, 'Cd-110': 0.1249,
'Cd-111': 0.128, 'Cd-112': 0.2413, 'Cd-113': 0.1222,
'Cd-114': 0.2873, 'Cd-116': 0.0749, 'In-113': 0.0429,
'In-115': 0.9571, 'Sn-112': 0.0097, 'Sn-114': 0.0066,
'Sn-115': 0.0034, 'Sn-116': 0.1454, 'Sn-117': 0.0768,
'Sn-118': 0.2422, 'Sn-119': 0.0859, 'Sn-120': 0.3258,
'Sn-122': 0.0463, 'Sn-124': 0.0579, 'Sb-121': 0.5721,
'Sb-123': 0.4279, 'Te-120': 0.0009, 'Te-122': 0.0255,
'Te-123': 0.0089, 'Te-124': 0.0474, 'Te-125': 0.0707,
'Te-126': 0.1884, 'Te-128': 0.3174, 'Te-130': 0.3408,
'I-127': 1.0, 'Xe-124': 0.000952, 'Xe-126': 0.00089,
'Xe-128': 0.019102, 'Xe-129': 0.264006, 'Xe-130': 0.04071,
'Xe-131': 0.212324, 'Xe-132': 0.269086, 'Xe-134': 0.104357,
'Xe-136': 0.088573, 'Cs-133': 1.0, 'Ba-130': 0.00106,
'Ba-132': 0.00101, 'Ba-134': 0.02417, 'Ba-135': 0.06592,
'Ba-136': 0.07854, 'Ba-137': 0.11232, 'Ba-138': 0.71698,
'La-138': 0.0008881, 'La-139': 0.9991119, 'Ce-136': 0.00185,
'Ce-138': 0.00251, 'Ce-140': 0.8845, 'Ce-142': 0.11114,
'Pr-141': 1.0, 'Nd-142': 0.27152, 'Nd-143': 0.12174,
'Nd-144': 0.23798, 'Nd-145': 0.08293, 'Nd-146': 0.17189,
'Nd-148': 0.05756, 'Nd-150': 0.05638, 'Sm-144': 0.0307,
'Sm-147': 0.1499, 'Sm-148': 0.1124, 'Sm-149': 0.1382,
'Sm-150': 0.0738, 'Sm-152': 0.2675, 'Sm-154': 0.2275,
'Eu-151': 0.4781, 'Eu-153': 0.5219, 'Gd-152': 0.002,
'Gd-154': 0.0218, 'Gd-155': 0.148, 'Gd-156': 0.2047,
'Gd-157': 0.1565, 'Gd-158': 0.2484, 'Gd-160': 0.2186,
'Tb-159': 1.0, 'Dy-156': 0.00056, 'Dy-158': 0.00095,
'Dy-160': 0.02329, 'Dy-161': 0.18889, 'Dy-162': 0.25475,
'Dy-163': 0.24896, 'Dy-164': 0.2826, 'Ho-165': 1.0,
'Er-162': 0.00139, 'Er-164': 0.01601, 'Er-166': 0.33503,
'Er-167': 0.22869, 'Er-168': 0.26978, 'Er-170': 0.1491,
'Tm-169': 1.0, 'Yb-168': 0.00123, 'Yb-170': 0.02982,
'Yb-171': 0.1409, 'Yb-172': 0.2168, 'Yb-173': 0.16103,
'Yb-174': 0.32026, 'Yb-176': 0.12996, 'Lu-175': 0.97401,
'Lu-176': 0.02599, 'Hf-174': 0.0016, 'Hf-176': 0.0526,
'Hf-177': 0.186, 'Hf-178': 0.2728, 'Hf-179': 0.1362,
'Hf-180': 0.3508, 'Ta-180': 0.0001201, 'Ta-181': 0.9998799,
'W-180': 0.0012, 'W-182': 0.265, 'W-183': 0.1431,
'W-184': 0.3064, 'W-186': 0.2843, 'Re-185': 0.374,
'Re-187': 0.626, 'Os-184': 0.0002, 'Os-186': 0.0159,
'Os-187': 0.0196, 'Os-188': 0.1324, 'Os-189': 0.1615,
'Os-190': 0.2626, 'Os-192': 0.4078, 'Ir-191': 0.373,
'Ir-193': 0.627, 'Pt-190': 0.00012, 'Pt-192': 0.00782,
'Pt-194': 0.3286, 'Pt-195': 0.3378, 'Pt-196': 0.2521,
'Pt-198': 0.07356, 'Au-197': 1.0, 'Hg-196': 0.0015,
'Hg-198': 0.0997, 'Hg-199': 0.1687, 'Hg-200': 0.231,
'Hg-201': 0.1318, 'Hg-202': 0.2986, 'Hg-204': 0.0687,
'Tl-203': 0.2952, 'Tl-205': 0.7048, 'Pb-204': 0.014,
'Pb-206': 0.241, 'Pb-207': 0.221, 'Pb-208': 0.524,
'Bi-209': 1.0, 'Th-232': 1.0, 'Pa-231': 1.0,
'U-234': 5.4e-05, 'U-235': 0.007204, 'U-238': 0.992742
}

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